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The GNU C++ Library Manual

i

The GNU C++ Library Manual

The GNU C++ Library Manual

ii

Copyright © 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017 FSF

The GNU C++ Library Manual

iii

COLLABORATORS
TITLE :
The GNU C++ Library Manual
ACTION

NAME

DATE

SIGNATURE

WRITTEN BY

, Paolo Carlini, Phil
Edwards, Doug
Gregor, Benjamin
Kosnik, Dhruv
Matani, Jason Merrill,
Mark Mitchell,
Nathan Myers, Felix
Natter, Stefan
Olsson, Silvius Rus,
Johannes Singler,
Ami Tavory, and
Jonathan Wakely

January 25, 2018

REVISION HISTORY
NUMBER

DATE

DESCRIPTION

NAME

The GNU C++ Library Manual

iv

Contents

I
1

Introduction
Status

2

1.1

Implementation Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2

1.1.1

C++ 1998/2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2

1.1.1.1

Implementation Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2

1.1.1.2

Implementation Specific Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2

C++ 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4

1.1.2.1

Implementation Specific Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4

1.1.3

C++ 2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6

1.1.4

C++ 2017 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8

1.1.4.1

8

1.1.2

1.1.5

1.3

Implementation Specific Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

1.1.6

C++ TR 24733 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

1.1.7

C++ IS 29124 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.1.7.1

1.2

Implementation Specific Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

C++ TR1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.1.5.1

2

1

Implementation Specific Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

License . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.2.1

The Code: GPL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

1.2.2

The Documentation: GPL, FDL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Bugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
1.3.1

Implementation Bugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

1.3.2

Standard Bugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Setup

22

2.1

Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

2.2

Configure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

2.3

Make . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

The GNU C++ Library Manual

3

Using

v

27

3.1

Command Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

3.2

Headers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.2.1

Header Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

3.2.2

Mixing Headers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

3.2.3

The C Headers and namespace std . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

3.2.4

Precompiled Headers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

3.3

Macros . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

3.4

Dual ABI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.4.1

3.5

3.6

3.7

Namespaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.5.1

Available Namespaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

3.5.2

namespace std . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

3.5.3

Using Namespace Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Linking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.6.1

Almost Nothing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

3.6.2

Finding Dynamic or Shared Libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

3.6.3

Experimental Library Extensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Concurrency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.7.1

Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

3.7.2

Thread Safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

3.7.3

Atomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

3.7.4

IO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

3.7.5
3.8

3.7.4.1

Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

3.7.4.2

Defaults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

3.7.4.3

Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

3.7.4.4

Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Containers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.8.1

Exception Safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

3.8.2

Exception Neutrality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

3.8.3

Doing without . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

3.8.4

Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

3.8.5
3.9

Troubleshooting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

3.8.4.1

With C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

3.8.4.2

With POSIX thread cancellation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Debugging Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
3.9.1

Using g++ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

3.9.2

Debug Versions of Library Binary Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

The GNU C++ Library Manual

II
4

5

Memory Leak Hunting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

3.9.4

Data Race Hunting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

3.9.5

Using gdb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

3.9.6

Tracking uncaught exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

3.9.7

Debug Mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

3.9.8

Compile Time Checking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

3.9.9

Profile-based Performance Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Support

46
47

Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.1.1

Fundamental Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

4.1.2

Numeric Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

4.1.3

NULL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

4.2

Dynamic Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

4.3

Termination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
4.3.1

Termination Handlers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

4.3.2

Verbose Terminate Handler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Diagnostics
5.1

6

3.9.3

Standard Contents

4.1

vi

52

Exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
5.1.1

API Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

5.1.2

Adding Data to exception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

5.2

Use of errno by the library . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

5.3

Concept Checking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Utilities

54

6.1

Functors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

6.2

Pairs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

6.3

Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
6.3.1

Allocators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
6.3.1.1

Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

6.3.1.2

Design Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

6.3.1.3

Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
6.3.1.3.1

Interface Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

6.3.1.3.2

Selecting Default Allocation Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

6.3.1.3.3

Disabling Memory Caching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

6.3.1.4

Using a Specific Allocator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

6.3.1.5

Custom Allocators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

The GNU C++ Library Manual

6.3.2

6.3.3

6.3.1.6

Extension Allocators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

6.3.1.7

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

auto_ptr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
6.3.2.1

Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

6.3.2.2

Use in Containers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

shared_ptr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
6.3.3.1

Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

6.3.3.2

Design Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

6.3.3.3

Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

6.3.3.4

6.4
7

8

6.3.3.3.1

Class Hierarchy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

6.3.3.3.2

Thread Safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

6.3.3.3.3

Selecting Lock Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

6.3.3.3.4

Related functions and classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
6.3.3.4.1

Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

6.3.3.4.2

Unresolved Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

6.3.3.5

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

6.3.3.6

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Strings
7.1

64

String Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
7.1.1

Simple Transformations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

7.1.2

Case Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

7.1.3

Arbitrary Character Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

7.1.4

Tokenizing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

7.1.5

Shrink to Fit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

7.1.6

CString (MFC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Localization
8.1

70

Locales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
8.1.1

locale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
8.1.1.1

Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

8.1.1.2

Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

8.1.1.3

Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
8.1.1.3.1

8.2

vii

Interacting with "C" locales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

8.1.1.4

Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

8.1.1.5

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

Facets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

The GNU C++ Library Manual

8.2.1

ctype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
8.2.1.1

Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
8.2.1.1.1

8.2.2

8.2.3

9

Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

8.2.1.3

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

codecvt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
8.2.2.1

Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

8.2.2.2

Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

8.2.2.2.2

Support for Unicode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

8.2.2.2.3

Other Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

8.2.2.4

Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

8.2.2.5

Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

8.2.2.6

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

messages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
8.2.3.1

Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

8.2.3.2

Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

8.2.3.3

Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
8.2.3.3.1

Models

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

8.2.3.3.2

The GNU Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

8.2.3.4

Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

8.2.3.5

Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

8.2.3.6

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
87

list . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
list::size() is O(n) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Associative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
9.2.1

Insertion Hints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

9.2.2

bitset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
9.2.2.1

Size Variable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

9.2.2.2

Type String . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

Unordered Associative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
9.3.1

Insertion Hints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

9.3.2

Hash Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
9.3.2.1

9.4

wchar_t Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

8.2.2.3

9.1.1.1

9.3

8.2.2.2.1

Sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
9.1.1

9.2

Specializations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

8.2.1.2

Containers
9.1

viii

Hash Code Caching Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90

Interacting with C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
9.4.1

Containers vs. Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

The GNU C++ Library Manual

10 Iterators

ix

93

10.1 Predefined . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
10.1.1 Iterators vs. Pointers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
10.1.2 One Past the End . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
11 Algorithms

95

11.1 Mutating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
11.1.1 swap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
11.1.1.1 Specializations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
12 Numerics

96

12.1 Complex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
12.1.1 complex Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
12.2 Generalized Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
12.3 Interacting with C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
12.3.1 Numerics vs. Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
12.3.2 C99 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
13 Input and Output

98

13.1 Iostream Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
13.2 Stream Buffers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
13.2.1 Derived streambuf Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
13.2.2 Buffering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
13.3 Memory Based Streams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
13.3.1 Compatibility With strstream . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
13.4 File Based Streams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
13.4.1 Copying a File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
13.4.2 Binary Input and Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
13.5 Interacting with C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
13.5.1 Using FILE* and file descriptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
13.5.2 Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
14 Atomics

105

14.1 API Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
15 Concurrency

106

15.1 API Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

III

Extensions

107

16 Compile Time Checks

109

The GNU C++ Library Manual

17 Debug Mode

x

110

17.1 Intro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
17.2 Semantics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
17.3 Using . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
17.3.1 Using the Debug Mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
17.3.2 Using a Specific Debug Container . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
17.4 Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
17.4.1 Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
17.4.2 Methods

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

17.4.2.1 The Wrapper Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
17.4.2.1.1

Safe Iterators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

17.4.2.1.2

Safe Sequences (Containers) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

17.4.2.2 Precondition Checking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
17.4.2.3 Release- and debug-mode coexistence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
17.4.2.3.1

Compile-time coexistence of release- and debug-mode components . . . . . . . . . . 115

17.4.2.3.2

Link- and run-time coexistence of release- and debug-mode components . . . . . . . 116

17.4.2.3.3

Alternatives for Coexistence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117

17.4.3 Other Implementations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
18 Parallel Mode

119

18.1 Intro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
18.2 Semantics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
18.3 Using . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
18.3.1 Prerequisite Compiler Flags . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
18.3.2 Using Parallel Mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
18.3.3 Using Specific Parallel Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
18.4 Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
18.4.1 Interface Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
18.4.2 Configuration and Tuning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
18.4.2.1 Setting up the OpenMP Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
18.4.2.2 Compile Time Switches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
18.4.2.3 Run Time Settings and Defaults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
18.4.3 Implementation Namespaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
18.5 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
18.6 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

The GNU C++ Library Manual

19 Profile Mode

xi

126

19.1 Intro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
19.1.1 Using the Profile Mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
19.1.2 Tuning the Profile Mode . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
19.2 Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
19.2.1 Wrapper Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
19.2.2 Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
19.2.3 Run Time Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
19.2.4 Analysis and Diagnostics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
19.2.5 Cost Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
19.2.6 Reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
19.2.7 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
19.3 Extensions for Custom Containers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
19.4 Empirical Cost Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
19.5 Implementation Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
19.5.1 Stack Traces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
19.5.2 Symbolization of Instruction Addresses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
19.5.3 Concurrency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
19.5.4 Using the Standard Library in the Instrumentation Implementation . . . . . . . . . . . . . . . . . . . . . 130
19.5.5 Malloc Hooks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
19.5.6 Construction and Destruction of Global Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
19.6 Developer Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
19.6.1 Big Picture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
19.6.2 How To Add A Diagnostic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
19.7 Diagnostics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
19.7.1 Diagnostic Template . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
19.7.2 Containers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
19.7.2.1 Hashtable Too Small . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
19.7.2.2 Hashtable Too Large . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
19.7.2.3 Inefficient Hash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
19.7.2.4 Vector Too Small . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
19.7.2.5 Vector Too Large . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
19.7.2.6 Vector to Hashtable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
19.7.2.7 Hashtable to Vector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
19.7.2.8 Vector to List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
19.7.2.9 List to Vector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
19.7.2.10 List to Forward List (Slist) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
19.7.2.11 Ordered to Unordered Associative Container . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
19.7.3 Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138

The GNU C++ Library Manual

xii

19.7.3.1 Sort Algorithm Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
19.7.4 Data Locality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
19.7.4.1 Need Software Prefetch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
19.7.4.2 Linked Structure Locality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
19.7.5 Multithreaded Data Access . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
19.7.5.1 Data Dependence Violations at Container Level . . . . . . . . . . . . . . . . . . . . . . . . . 140
19.7.5.2 False Sharing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
19.7.6 Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
19.8 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
20 The mt_allocator

142

20.1 Intro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
20.2 Design Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
20.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
20.3 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
20.3.1 Tunable Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
20.3.2 Initialization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
20.3.3 Deallocation Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
20.4 Single Thread Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
20.5 Multiple Thread Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
21 The bitmap_allocator

148

21.1 Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
21.2 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
21.2.1 Free List Store . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
21.2.2 Super Block . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
21.2.3 Super Block Data Layout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
21.2.4 Maximum Wasted Percentage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
21.2.5 allocate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
21.2.6 deallocate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
21.2.7 Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
21.2.7.1 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
21.2.7.2 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
21.2.7.3 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
21.2.8 Locality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
21.2.9 Overhead and Grow Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152

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22 Policy-Based Data Structures

153

22.1 Intro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
22.1.1 Performance Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
22.1.1.1 Associative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
22.1.1.2 Priority Que . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
22.1.2 Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
22.1.2.1 Associative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
22.1.2.1.1

Policy Choices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154

22.1.2.1.2

Underlying Data Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155

22.1.2.1.3

Iterators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157

22.1.2.1.3.1

Using Point Iterators for Range Operations . . . . . . . . . . . . . . . . . . . 158

22.1.2.1.3.2

Cost to Point Iterators to Enable Range Operations . . . . . . . . . . . . . . 158

22.1.2.1.3.3

Invalidation Guarantees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

22.1.2.1.4

Functional . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161

22.1.2.1.4.1

erase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161

22.1.2.1.4.2

split and join . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162

22.1.2.1.4.3

insert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162

22.1.2.1.4.4

operator== and operator<=

. . . . . . . . . . . . . . . . . . . . . . 162

22.1.2.2 Priority Queues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
22.1.2.2.1

Policy Choices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162

22.1.2.2.2

Underlying Data Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163

22.1.2.2.3

Binary Heaps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164

22.2 Using . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
22.2.1 Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
22.2.2 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
22.2.3 Tutorial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
22.2.3.1 Basic Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
22.2.3.2

Configuring via Template Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168

22.2.3.3

Querying Container Attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168

22.2.3.4

Point and Range Iteration

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169

22.2.4 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
22.2.4.1 Intermediate Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
22.2.4.2 Querying with container_traits

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170

22.2.4.3 By Container Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
22.2.4.3.1

Hash-Based . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

22.2.4.3.1.1

size Related . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

22.2.4.3.1.2

Hashing Function Related . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

22.2.4.3.2

Branch-Based . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

22.2.4.3.2.1

split or join Related . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

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22.2.4.3.2.2

Node Invariants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

22.2.4.3.2.3

trie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

22.2.4.3.3

Priority Queues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171

22.3 Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
22.3.1 Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
22.3.1.1 Null Policy Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
22.3.1.2 Map and Set Semantics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
22.3.1.2.1

Distinguishing Between Maps and Sets . . . . . . . . . . . . . . . . . . . . . . . . 172

22.3.1.2.2

Alternatives to std::multiset and std::multimap . . . . . . . . . . . . . . 173

22.3.1.3 Iterator Semantics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
22.3.1.3.1

Point and Range Iterators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176

22.3.1.3.2

Distinguishing Point and Range Iterators . . . . . . . . . . . . . . . . . . . . . . . . 176

22.3.1.3.3

Invalidation Guarantees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177

22.3.1.4 Genericity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
22.3.1.4.1

Tag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179

22.3.1.4.2

Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180

22.3.2 By Container . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
22.3.2.1 hash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
22.3.2.1.1

Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180

22.3.2.1.2

Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181

22.3.2.1.2.1

Hash Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181

22.3.2.1.2.2

General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181

22.3.2.1.2.3

Range Hashing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

22.3.2.1.2.4

Ranged Hash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184

22.3.2.1.2.5

Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184

22.3.2.1.2.6

Range-Hashing and Ranged-Hashes in Collision-Chaining Tables . . . . . . 185

22.3.2.1.2.7

Probing tables

22.3.2.1.2.8

Pre-Defined Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186

22.3.2.1.2.9

Resize Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186

22.3.2.1.2.10 General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
22.3.2.1.2.11 Size Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
22.3.2.1.2.12 Trigger Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
22.3.2.1.2.13 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
22.3.2.1.2.14 Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
22.3.2.1.2.15 Predefined Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
22.3.2.1.2.16 Controling Access to Internals . . . . . . . . . . . . . . . . . . . . . . . . . 194
22.3.2.1.2.17 Policy Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
22.3.2.1.2.18 probe/size/trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
22.3.2.1.2.19 hash/trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195

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22.3.2.1.2.20 equivalence functors/storing hash values/hash . . . . . . . . . . . . . . . . . 195
22.3.2.1.2.21 size/load-check trigger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
22.3.2.2 tree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
22.3.2.2.1

Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195

22.3.2.2.2

Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196

22.3.2.2.2.1

Node Invariants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196

22.3.2.2.2.2

Node Iterators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199

22.3.2.2.2.3

Node Updator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199

22.3.2.2.2.4

Split and Join . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204

22.3.2.3 Trie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
22.3.2.3.1

Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204

22.3.2.3.2

Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205

22.3.2.3.2.1

Element Access Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205

22.3.2.3.2.2

Node Invariants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206

22.3.2.3.2.3

Split and Join . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207

22.3.2.4 List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
22.3.2.4.1

Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207

22.3.2.4.2

Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208

22.3.2.4.2.1

Underlying Data Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . 208

22.3.2.4.2.2

Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209

22.3.2.4.2.3

Use in Multimaps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210

22.3.2.5 Priority Queue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210
22.3.2.5.1

Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210

22.3.2.5.2

Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211

22.3.2.5.2.1

Iterators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211

22.3.2.5.2.2

Underlying Data Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . 212

22.3.2.5.2.3

Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213

22.4 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
22.4.1 Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
22.4.2 Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
22.4.2.1 Hash-Based . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
22.4.2.1.1

Text find . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214

22.4.2.1.1.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214

22.4.2.1.1.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215

22.4.2.1.1.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216

22.4.2.1.2

Integer find . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216

22.4.2.1.2.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216

22.4.2.1.2.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216

22.4.2.1.2.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219

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xvi

Integer Subscript find

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219

22.4.2.1.3.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219

22.4.2.1.3.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219

22.4.2.1.3.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222

22.4.2.1.4

Integer Subscript insert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222

22.4.2.1.4.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222

22.4.2.1.4.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222

22.4.2.1.4.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225

22.4.2.1.5

Integer find with Skewed-Distribution

. . . . . . . . . . . . . . . . . . . . . . . 225

22.4.2.1.5.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225

22.4.2.1.5.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226

22.4.2.1.5.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227

22.4.2.1.6

Erase Memory Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227

22.4.2.1.6.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227

22.4.2.1.6.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227

22.4.2.1.6.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229

22.4.2.2 Branch-Based . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229
22.4.2.2.1

Text insert

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229

22.4.2.2.1.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229

22.4.2.2.1.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229

22.4.2.2.1.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231

22.4.2.2.2

Text find . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231

22.4.2.2.2.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231

22.4.2.2.2.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232

22.4.2.2.2.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232

22.4.2.2.3

Text find with Locality-of-Reference . . . . . . . . . . . . . . . . . . . . . . . . 233

22.4.2.2.3.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233

22.4.2.2.3.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233

22.4.2.2.3.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234

22.4.2.2.4

split and join . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234

22.4.2.2.4.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234

22.4.2.2.4.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234

22.4.2.2.4.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235

22.4.2.2.5

Order-Statistics

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236

22.4.2.2.5.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236

22.4.2.2.5.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236

22.4.2.2.5.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237

22.4.2.3 Multimap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
22.4.2.3.1

Text find with Small Secondary-to-Primary Key Ratios

. . . . . . . . . . . . . . 237

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22.4.2.3.1.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237

22.4.2.3.1.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237

22.4.2.3.1.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240

22.4.2.3.2

Text find with Large Secondary-to-Primary Key Ratios

. . . . . . . . . . . . . . 241

22.4.2.3.2.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241

22.4.2.3.2.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241

22.4.2.3.2.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244

22.4.2.3.3

Text insert with Small Secondary-to-Primary Key Ratios . . . . . . . . . . . . . 244

22.4.2.3.3.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244

22.4.2.3.3.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244

22.4.2.3.3.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247

22.4.2.3.4

Text insert with Small Secondary-to-Primary Key Ratios . . . . . . . . . . . . . 248

22.4.2.3.4.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248

22.4.2.3.4.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248

22.4.2.3.4.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251

22.4.2.3.5

Text insert with Small Secondary-to-Primary Key Ratios Memory Use

. . . . . 251

22.4.2.3.5.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251

22.4.2.3.5.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251

22.4.2.3.5.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254

22.4.2.3.6

Text insert with Small Secondary-to-Primary Key Ratios Memory Use

. . . . . 255

22.4.2.3.6.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255

22.4.2.3.6.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255

22.4.2.3.6.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258

22.4.2.4 Priority Queue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258
22.4.2.4.1

Text push . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258

22.4.2.4.1.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258

22.4.2.4.1.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258

22.4.2.4.1.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260

22.4.2.4.2

Text push and pop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260

22.4.2.4.2.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260

22.4.2.4.2.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261

22.4.2.4.2.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 262

22.4.2.4.3

Integer push . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 262

22.4.2.4.3.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 262

22.4.2.4.3.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263

22.4.2.4.3.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264

22.4.2.4.4

Integer push . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264

22.4.2.4.4.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264

22.4.2.4.4.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 264

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22.4.2.4.4.3
22.4.2.4.5

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265

Text pop Memory Use

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266

22.4.2.4.5.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266

22.4.2.4.5.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266

22.4.2.4.5.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267

22.4.2.4.6

Text join . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267

22.4.2.4.6.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267

22.4.2.4.6.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267

22.4.2.4.6.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268

22.4.2.4.7

Text modify Up

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269

22.4.2.4.7.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269

22.4.2.4.7.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269

22.4.2.4.7.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270

22.4.2.4.8

Text modify Down . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271

22.4.2.4.8.1

Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271

22.4.2.4.8.2

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271

22.4.2.4.8.3

Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272

22.4.2.5 Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273
22.4.2.5.1

Associative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273

22.4.2.5.1.1

Underlying Data-Structure Families . . . . . . . . . . . . . . . . . . . . . . 273

22.4.2.5.1.2

Hash-Based Containers

22.4.2.5.1.3

Hash Policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273

22.4.2.5.1.4

Branch-Based Containers

22.4.2.5.1.5

Mapping-Semantics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274

22.4.2.5.2

. . . . . . . . . . . . . . . . . . . . . . . . . . . . 273

. . . . . . . . . . . . . . . . . . . . . . . . . . . 273

Priority_Queue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275

22.4.2.5.2.1

Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275

22.4.2.5.2.2

Amortized push and pop operations . . . . . . . . . . . . . . . . . . . . . 276

22.4.2.5.2.3

Graph Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276

22.5 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276
22.6 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277
23 HP/SGI Extensions

279

23.1 Backwards Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279
23.2 Deprecated . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279
24 Utilities

281

25 Algorithms

282

26 Numerics

283

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27 Iterators

284

28 Input and Output

285

28.1 Derived filebufs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285
29 Demangling

286

30 Concurrency

288

30.1 Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288
30.1.1 Interface to Locks and Mutexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288
30.1.2 Interface to Atomic Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288
30.2 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289
30.2.1 Using Built-in Atomic Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289
30.2.2 Thread Abstraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 290
30.3 Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291

IV
A

Appendices

292

Contributing

293

A.1 Contributor Checklist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293
A.1.1 Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293
A.1.2 Assignment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293
A.1.3 Getting Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293
A.1.4 Submitting Patches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294
A.2 Directory Layout and Source Conventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294
A.3 Coding Style . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295
A.3.1 Bad Identifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295
A.3.2 By Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298
A.4 Design Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306
B

Porting and Maintenance

322

B.1 Configure and Build Hacking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322
B.1.1

Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322

B.1.2

Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322

B.1.3

B.1.2.1

General Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322

B.1.2.2

What Comes from Where . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323

Configure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323
B.1.3.1

Storing Information in non-AC files (like configure.host) . . . . . . . . . . . . . . . . . . . . 323

B.1.3.2

Coding and Commenting Conventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323

B.1.3.3

The acinclude.m4 layout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323

B.1.3.4

GLIBCXX_ENABLE, the --enable maker . . . . . . . . . . . . . . . . . . . . . . . . . . . 325

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B.1.3.5
B.1.4

xx

Shared Library Versioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 326

Make . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327

B.2 Writing and Generating Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327
B.2.1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327

B.2.2

Generating Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327

B.2.3

Doxygen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328

B.2.4

B.2.3.1

Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328

B.2.3.2

Generating the Doxygen Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328

B.2.3.3

Debugging Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329

B.2.3.4

Markup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330

Docbook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331
B.2.4.1

Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331

B.2.4.2

Generating the DocBook Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331

B.2.4.3

Debugging Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332

B.2.4.4

Editing and Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332

B.2.4.5

File Organization and Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333

B.2.4.6

Markup By Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334

B.3 Porting to New Hardware or Operating Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334
B.3.1

Operating System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335

B.3.2

CPU . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336

B.3.3

Character Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336

B.3.4

Thread Safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339

B.3.5

Numeric Limits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340

B.3.6

Libtool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340

B.4 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340
B.4.1

B.4.2

B.4.3

B.4.4

B.4.5

Test Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340
B.4.1.1

Directory Layout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340

B.4.1.2

Naming Conventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341

Running the Testsuite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 342
B.4.2.1

Basic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 342

B.4.2.2

Variations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 342

B.4.2.3

Permutations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344

Writing a new test case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344
B.4.3.1

Examples of Test Directives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346

B.4.3.2

Directives Specific to Libstdc++ Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346

Test Harness and Utilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347
B.4.4.1

DejaGnu Harness Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347

B.4.4.2

Utilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347

Special Topics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348

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B.4.5.1

xxi

Qualifying Exception Safety Guarantees

. . . . . . . . . . . . . . . . . . . . . . . . . . . . 348

B.4.5.1.1

Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348

B.4.5.1.2

Existing tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 349

B.4.5.1.3

C++11 Requirements Test Sequence Descriptions

. . . . . . . . . . . . . . . . . . 349

B.5 ABI Policy and Guidelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350
B.5.1

The C++ Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350

B.5.2

Versioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350
B.5.2.1

Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350

B.5.2.2

History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350

B.5.2.3

Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356

B.5.2.4

Configuring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357

B.5.2.5

Checking Active . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357

B.5.3

Allowed Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358

B.5.4

Prohibited Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358

B.5.5

Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358

B.5.6

Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359
B.5.6.1

Single ABI Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359

B.5.6.2

Multiple ABI Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360

B.5.7

Outstanding Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361

B.5.8

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361

B.6 API Evolution and Deprecation History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361
B.6.1

3.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361

B.6.2

3.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362

B.6.3

3.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362

B.6.4

3.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362

B.6.5

3.4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362

B.6.6

4.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363

B.6.7

4.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363

B.6.8

4.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363

B.6.9

4.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364

B.6.10 4.4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365
B.6.11 4.5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365
B.6.12 4.6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366
B.6.13 4.7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366
B.6.14 4.8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366
B.6.15 4.9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366
B.6.16 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366
B.7 Backwards Compatibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367
B.7.1

First . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367

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xxii

B.7.1.1

No ios_base . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367

B.7.1.2

No cout in , no cin in  . . . . . . . . . . . . . . . . . . . . 367

Second . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367
B.7.2.1

Namespace std:: not supported . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367

B.7.2.2

Illegal iterator usage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 368

B.7.2.3

isspace from  is a macro

B.7.2.4

No vector::at, deque::at, string::at . . . . . . . . . . . . . . . . . . . . . . . . 369

B.7.2.5

No std::char_traits::eof . . . . . . . . . . . . . . . . . . . . . . . . . . . 369

B.7.2.6

No string::clear . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369

B.7.2.7

Removal of ostream::form and istream::scan extensions . . . . . . . . . . . . . . 370

B.7.2.8

No basic_stringbuf, basic_stringstream . . . . . . . . . . . . . . . . . . . . . . 370

B.7.2.9

Little or no wide character support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 368

B.7.2.10 No templatized iostreams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371
B.7.2.11 Thread safety issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371
B.7.3

B.7.4

Third . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 372
B.7.3.1

Pre-ISO headers removed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 372

B.7.3.2

Extension headers hash_map, hash_set moved to ext or backwards . . . . . . . . . . . . . . . 372

B.7.3.3

No ios::nocreate/ios::noreplace. . . . . . . . . . . . . . . . . . . . . . . . . . . 374

B.7.3.4

No stream::attach(int fd)

B.7.3.5

Support for C++98 dialect. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 374

B.7.3.6

Support for C++TR1 dialect. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375

B.7.3.7

Support for C++11 dialect. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376

B.7.3.8

Container::iterator_type is not necessarily Container::value_type*

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 374

. . . 380

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380

C

Free Software Needs Free Documentation

382

D

GNU General Public License version 3

384

E GNU Free Documentation License

31 Index

393

399

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xxiii

List of Figures

22.1 Node Invariants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
22.2 Underlying Associative Data Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
22.3 Range Iteration in Different Data Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
22.4 Point Iteration in Hash Data Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
22.5 Effect of erase in different underlying data structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
22.6 Underlying Priority Queue Data Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
22.7 Exception Hierarchy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
22.8 Non-unique Mapping Standard Containers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
22.9 Effect of embedded lists in std::multimap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
22.10Non-unique Mapping Containers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
22.11Point Iterator Hierarchy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
22.12Invalidation Guarantee Tags Hierarchy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
22.13Container Tag Hierarchy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
22.14Hash functions, ranged-hash functions, and range-hashing functions . . . . . . . . . . . . . . . . . . . . . . . . 182
22.15Insert hash sequence diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
22.16Insert hash sequence diagram with a null policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
22.17Hash policy class diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
22.18Balls and bins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
22.19Insert resize sequence diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
22.20Standard resize policy trigger sequence diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
22.21Standard resize policy size sequence diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193
22.22Tree node invariants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
22.23Tree node invalidation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
22.24A tree and its update policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
22.25Restoring node invariants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
22.26Insert update sequence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201
22.27Useless update path . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
22.28A PATRICIA trie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
22.29A trie and its update policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
22.30A simple list . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208

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22.31The counter algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
22.32Underlying Priority-Queue Data-Structures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
22.33Priority-Queue Data-Structure Tags. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213
B.1 Configure and Build File Dependencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323

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xxv

List of Tables

1.1

C++ 1998/2003 Implementation Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3

1.2

C++ 2011 Implementation Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5

1.3

C++ 2014 Implementation Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7

1.4

C++ Technical Specifications Implementation Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8

1.5

C++ 2017 Implementation Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

9

1.6

C++ Technical Specifications Implementation Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

1.7

C++ TR1 Implementation Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

1.8

C++ TR 24733 Implementation Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

1.9

C++ Special Functions Implementation Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.1

C++ Command Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

3.2

C++ 1998 Library Headers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

3.3

C++ 1998 Library Headers for C Library Facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

3.4

C++ 2011 Library Headers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

3.5

C++ 2011 Library Headers for C Library Facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.6

C++ TR 1 Library Headers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.7

C++ TR 1 Library Headers for C Library Facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.8

C++ TR 24733 Decimal Floating-Point Header . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.9

C++ ABI Headers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.10 Extension Headers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.11 Extension Debug Headers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.12 Extension Profile Headers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.13 Extension Parallel Headers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
17.1 Debugging Containers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
17.2 Debugging Containers C++11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
18.1 Parallel Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
19.1 Profile Code Location . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
19.2 Profile Diagnostics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132

The GNU C++ Library Manual

xxvi

21.1 Bitmap Allocator Memory Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
B.1 Doxygen Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328
B.2 HTML to Doxygen Markup Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331
B.3 Docbook Prerequisites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331
B.4 HTML to Docbook XML Markup Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334
B.5 Docbook XML Element Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335
B.6 Extension Allocators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363
B.7 Extension Allocators Continued . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363

The GNU C++ Library Manual

1 / 399

Part I

Introduction

The GNU C++ Library Manual

2 / 399

Chapter 1

Status
1.1

Implementation Status

1.1.1

C++ 1998/2003

1.1.1.1

Implementation Status

This status table is based on the table of contents of ISO/IEC 14882:2003.
This page describes the C++ support in the GCC 7 series.
1.1.1.2

Implementation Specific Behavior

The ISO standard defines the following phrase:

[1.3.5] implementation-defined behavior Behavior, for a well-formed program construct and correct data, that depends on the implementation and that each implementation shall document.
We do so here, for the C++ library only. Behavior of the compiler, linker, runtime loader, and other elements of "the implementation" are documented elsewhere. Everything listed in Annex B, Implementation Qualities, are also part of the compiler, not the
library.
For each entry, we give the section number of the standard, when applicable. This list is probably incomplet and inkorrekt.
[1.9]/11 #3 If isatty(3) is true, then interactive stream support is implied.
[17.4.4.5] Non-reentrant functions are probably best discussed in the various sections on multithreading (see above).
[18.1]/4 The type of NULL is described under Support.
[18.3]/8 Even though it’s listed in the library sections, libstdc++ has zero control over what the cleanup code hands back to the
runtime loader. Talk to the compiler people. :-)
[18.4.2.1]/5 (bad_alloc), [18.5.2]/5 (bad_cast), [18.5.3]/5 (bad_typeid), [18.6.1]/8 (exception), [18.6.2.1]/5 (bad_exception):
The what() member function of class std::exception, and these other classes publicly derived from it, returns the name
of the class, e.g. "std::bad_alloc".
[18.5.1]/7 The return value of std::type_info::name() is the mangled type name. You will need to call c++filt and
pass the names as command-line parameters to demangle them, or call a runtime demangler function.
[20.1.5]/5 "Implementors are encouraged to supply libraries that can accept allocators that encapsulate more general memory
models and that support non-equal instances. In such implementations, any requirements imposed on allocators by containers

The GNU C++ Library Manual

Section
18
18.1
18.2
18.2.1
18.2.1.1
18.2.1.2
18.2.1.3
18.2.1.4
18.2.1.5
18.2.2
18.3
18.4
18.5
18.5.1
18.5.2
18.5.3
18.6
18.6.1
18.6.2
18.6.3
18.6.4
18.7
19
19.1
19.2
19.3
20
20.1
20.2
20.2.1
20.2.2
20.3
20.3.1
20.3.2
20.3.3
20.3.4
20.3.5
20.3.6
20.3.7
20.3.8
20.4
20.4.1
20.4.2
20.4.3
20.4.4
20.4.4.1
20.4.4.2
20.4.4.3
20.4.5
20.4.6
21
21.1
21.1.1

3 / 399

Description
Language support
Types
Implementation properties
Numeric Limits
Class template
numeric_limits
numeric_limits
members
float_round_style
float_denorm_style
numeric_limits
specializations
C Library
Start and termination
Dynamic memory
management
Type identification
Class type_info
Class bad_cast
Class bad_typeid
Exception handling
Class exception
Violation
exception-specifications
Abnormal termination
uncaught_exception
Other runtime support
Diagnostics
Exception classes
Assertions
Error numbers
General utilities
Requirements
Utility components
Operators
pair
Function objects
Base
Arithmetic operation
Comparisons
Logical operations
Negators
Binders
Adaptors for pointers to
functions
Adaptors for pointers to
members
Memory
The default allocator
Raw storage iterator
Temporary buffers
Specialized algorithms
uninitialized_copy
uninitialized_fill
uninitialized_fil
l_n
Class template auto_ptr
C library
Strings
Character traits
Character traits
requirements

Status
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y

Y

Comments

The GNU C++ Library Manual

4 / 399

beyond those requirements that appear in Table 32, and the semantics of containers and algorithms when allocator instances
compare non-equal, are implementation-defined." There is experimental support for non-equal allocators in the standard containers in C++98 mode. There are no additional requirements on allocators. It is undefined behaviour to swap two containers if their
allocators are not equal.
[21.1.3.1]/3,4, [21.1.3.2]/2, [21.3]/6 basic_string::iterator, basic_string::const_iterator, [23.*]’s foo::iterator, [27.*]’s foo::*_type,
others... Nope, these types are called implementation-defined because you shouldn’t be taking advantage of their underlying
types. Listing them here would defeat the purpose. :-)
[21.1.3.1]/5 I don’t really know about the mbstate_t stuff... see the codecvt notes for what does exist.
[22.*] Anything and everything we have on locale implementation will be described under Localization.
[26.2.8]/9 I have no idea what complex’s pow(0,0) returns.
[27.4.2.4]/2 Calling std::ios_base::sync_with_stdio after I/O has already been performed on the standard stream
objects will flush the buffers, and destroy and recreate the underlying buffer instances. Whether or not the previously-written
I/O is destroyed in this process depends mostly on the --enable-libio choice: for stdio, if the written data is already in the
stdio buffer, the data may be completely safe!
[27.6.1.1.2], [27.6.2.3] The I/O sentry ctor and dtor can perform additional work than the minimum required. We are not
currently taking advantage of this yet.
[27.7.1.3]/16, [27.8.1.4]/10 The effects of pubsetbuf/setbuf are described in the Input and Output chapter.
[27.8.1.4]/16 Calling fstream::sync when a get area exists will... whatever fflush() does, I think.

1.1.2

C++ 2011

This table is based on the table of contents of ISO/IEC JTC1 SC22 WG21 Doc No: N3290 Date: 2011-04-11 Final Draft
International Standard, Standard for Programming Language C++
In this implementation the -std=gnu++11 or -std=c++11 flag must be used to enable language and library features. See
dialect options. The pre-defined symbol __cplusplus is used to check for the presence of the required flag.
This page describes the C++11 support in the GCC 7 series.
1.1.2.1

Implementation Specific Behavior

For behaviour which is also specified by the 1998 and 2003 standards, see C++ 1998/2003 Implementation Specific Behavior.
This section only documents behaviour which is new in the 2011 standard.
17.6.5.12 [res.on.exception.handling] There are no implementation-defined exception classes, only standard exception classes
(or classes derived from them) will be thrown.
17.6.5.14 [value.error.codes] The error_category for errors originating outside the OS, and the possible error code values
for each error category, should be documented here.
18.6.2.2 [new.badlength] what() returns "std::bad_array_new_length".
20.6.9.1 [allocator.member]/5 Over-aligned types are not supported by std::allocator.
20.7.2.2.1 [util.smartptr.shared.const] When a shared_ptr constructor fails bad_alloc (or types derived from it) will be
thrown, or when an allocator is passed to the constructor then any exceptions thrown by the allocator.
20.7.2.0 [util.smartptr.weakptr] what() returns "bad_weak_ptr".
20.8.9.1.3 [func.bind.place]/1 There are 29 placeholders defined and the placeholder types are CopyAssignable.
20.11.7.1 [time.clock.system]/3, /4 Time point values are truncated to time_t values. There is no loss of precision for conversions in the other direction.
20.15.7 [meta.trans]/2 aligned_storage does not support extended alignment.
21.2.3.2 [char.traits.specializations.char16_t], 21.2.3.3 [char.traits.specializations.char32_t] The types u16streampos and
u32streampos are both synonyms for fpos. The function eof returns int_type(-1).

The GNU C++ Library Manual

Section
18
18.1
18.2
18.3
18.3.2
18.3.2.3
18.3.2.4
18.3.2.5
18.3.2.6
18.3.2.7
18.3.3
18.4
18.4.1
18.5
18.6
18.7
18.7.1
18.7.2
18.7.3
18.8
18.8.1
18.8.2
18.8.3
18.8.4
18.8.5
18.8.6
18.9
18.9.1
18.9.2
18.9.3
18.10
19
19.1
19.2
19.3
19.4
19.5
19.5.1
19.5.2
19.5.3
19.5.4
19.5.5
20
20.1
20.2
20.2.1
20.2.2
20.2.3
20.2.4
20.3
20.3.1
20.3.2
20.3.3

5 / 399

Description
Language support
General
Types
Implementation properties
Numeric Limits
Class template
numeric_limits
numeric_limits
members
float_round_style
float_denorm_style
numeric_limits
specializations
C Library
Integer types
Header 
synopsis
Start and termination
Dynamic memory
management
Type identification
Class type_info
Class bad_cast
Class bad_typeid
Exception handling
Class exception
Class bad_exception
Abnormal termination
uncaught_exception
Exception Propagation
nested_exception
Initializer lists
Initializer list constructors
Initializer list access
Initializer list range access
Other runtime support
Diagnostics
General
Exception classes
Assertions
Error numbers
System error support
Class error_category
Class error_code
Class
error_condition
Comparison operators
Class system_error
General utilities
General
Utility components
Operators
Swap
forward and move
helpers
Function template
declval
Pairs
In general
Class template pair
Specialized algorithms

Status

Comments

Y
Y

Y
Y
N
N
Y
Y
Y
Partial
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y

Y
Y
Y
Y

Y
Y

C library dependency for
quick_exit, at_quick_exit

The GNU C++ Library Manual

6 / 399

22.3.1 [locale] There is one global locale for the whole program, not per-thread.
22.4.5.1.2 [locale.time.get.virtuals], 22.4.5.3.2 [locale.time.put.virtuals] Additional supported formats should be documented
here.
22.4.7.1.2 [locale.messages.virtuals] The mapping should be documented here.
23.3.2.1 [array.overview] array::iterator is T* and array::const_iterator is const T*.
23.5.4.2 [unord.map.cnstr], 23.5.5.2 [unord.multimap.cnstr], 23.5.6.2 [unord.set.cnstr], 23.5.7.2 [unord.multiset.cnstr] The default minimal bucket count is 0 for the default constructors, range constructors and initializer-list constructors.
25.3.12 [alg.random.shuffle] The two-argument overload of random_shuffle uses rand as the source of randomness.
26.5.5 [rand.predef] The type default_random_engine is a synonym for minstd_rand0.
26.5.6 [rand.device] The default token argument to the random_device constructor is "default". Other valid arguments
are "/dev/random" and "/dev/urandom", which determine the character special file to read random bytes from. The "de
fault" token will read bytes from a hardware RNG if available (currently this only supports the IA-32 RDRAND instruction)
otherwise it is equivalent to "/dev/urandom". An exception of type runtime_error will be thrown if a random_dev
ice object cannot open or read from the source of random bytes.
26.5.8.1 [rand.dist.general] The algorithms used by the distributions should be documented here.
26.8 [c.math] Whether the rand function introduces data races depends on the C library as the function is not provided by
libstdc++.
27.8.2.1 [stringbuf.cons] Whether the sequence pointers are copied by the basic_stringbuf move constructor should be
documented here.
27.9.1.2 [filebuf.cons] Whether the sequence pointers are copied by the basic_filebuf move constructor should be documented here.
28.5.1 [re.synopt], 28.5.2 [re.matchflag] , 28.5.3 [re.err] syntax_option_type, match_flag_type and error_type
are unscoped enumeration types.
28.7 [re.traits] The blank character class corresponds to the ctype_base::blank mask.
29.4 [atomics.lockfree] The values of the ATOMIC_xxx_LOCK_FREE macros depend on the target and cannot be listed here.
30.2.3 [thread.req.native]/1 native_handle_type and native_handle are provided. The handle types are defined in
terms of the Gthreads abstraction layer, although this is subject to change at any time. Any use of native_handle is inherently
non-portable and not guaranteed to work between major releases of GCC.
• thread: The native handle type is a typedef for __gthread_t i.e. pthread_t when GCC is configured with the posix
thread model. The value of the native handle is undefined for a thread which is not joinable.
• mutex and timed_mutex: The native handle type is __gthread_mutex_t* i.e. pthread_mutex_t* for the posix
thread model.
• recursive_mutex and recursive_timed_mutex: The native handle type is __gthread_recursive_mutex
_t* i.e. pthread_mutex_t* for the posix thread model.
• condition_variable: The native handle type is __gthread_cond_t* i.e. pthread_cond_t* for the posix
thread model.
30.6.1 [futures.overview]/2 launch is a scoped enumeration type with overloaded operators to support bitmask operations.
There are no additional bitmask elements defined.

1.1.3

C++ 2014

In this implementation the -std=gnu++14 or -std=c++14 flag must be used to enable language and library features. See
dialect options. The pre-defined symbol __cplusplus is used to check for the presence of the required flag.
This page describes the C++14 and library TS support in the GCC 7 series.

The GNU C++ Library Manual

Paper
N3669
N3668
N3670
N3656
N3462
N3545
N3642
N3671
N3654
N3469
N3470
N3471
N3658
N3659
N3421
N3657
N3655
N3644

7 / 399

Title
Fixing constexpr member
functions without const
exchange() utility
function
Wording for Addressing
Tuples by Type
make_unique
std::result_of and
SFINAE
An Incremental
Improvement to
integral_constant
User-defined Literals for
Standard Library Types
Making non-modifying
sequence operations more
robust
Quoted Strings Library
Proposal
Constexpr Library
Additions: chrono
Constexpr Library
Additions: containers
Constexpr Library
Additions: utilities
Compile-time integer
sequences
Shared Locking in C++
Making Operator Functors
greater<>
Adding heterogeneous
comparison lookup to
associative containers
TransformationTraits Redux
Null Forward Iterators

Status

Comments

Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Partial

Table 1.3: C++ 2014 Implementation Status

Only affects Debug Mode

The GNU C++ Library Manual

Paper
N3662
N3793
N3804
N3866
N3905
N3915
N3916
N3920
N3921
N3925
N3932
N4100

8 / 399

Title
C++ Dynamic Arrays
A proposal to add a utility
class to represent optional
objects
Any library proposal
Invocation type traits, but
dropping
function_call_operator.
Faster string searching
(Boyer-Moore et al.)
apply() call a function with
arguments from a tuple
Polymorphic memory
resources
Extending shared_ptr to
support arrays
string_view: a
non-owning reference to a
string
A sample proposal
Variable Templates For
Type Traits
File System

Status
N

Comments
Array Extensions TS

Y

Library Fundamentals TS

Y

Library Fundamentals TS

N

Library Fundamentals TS

Y

Library Fundamentals TS

Y

Library Fundamentals TS

Partial

Library Fundamentals TS

Y

Library Fundamentals TS

Y

Library Fundamentals TS

Y

Library Fundamentals TS

Y

Library Fundamentals TS

Y

Link with -lstdc++fs

Table 1.4: C++ Technical Specifications Implementation Status

1.1.4

C++ 2017

In this implementation the -std=gnu++17 or -std=c++17 flag must be used to enable language and library features. See
dialect options. The pre-defined symbol __cplusplus is used to check for the presence of the required flag.
This section describes the C++17 and library TS support in the GCC 7 series.
The following table lists new library features that have been accepted into the C++17 working draft. The "Proposal" column
provides a link to the ISO C++ committee proposal that describes the feature, while the "Status" column indicates the first
version of GCC that contains an implementation of this feature (if it has been implemented). The "SD-6 Feature Test" column
shows the corresponding macro or header from SD-6: Feature-testing recommendations for C++.
Note 1: This feature is supported in GCC 7.1 and 7.2 but before GCC 7.3 the __cpp_lib macro is not defined, and compilation
will fail if the header is included without using -std to enable C++17 support.
Note 2: This feature is supported in older releases but the __cpp_lib macro is not defined to the right value (or not defined at
all) until the version shown in parentheses.
Note 3: The mathematical special functions are enabled in C++17 mode from GCC 7.1 onwards. For GCC 6.x or for C++11/C++14
define __STDCPP_WANT_MATH_SPEC_FUNCS__ to a non-zero value and test for __STDCPP_MATH_SPEC_FUNCS__ >=
201003L.
1.1.4.1

Implementation Specific Behavior

For behaviour which is also specified by previous standards, see C++ 1998/2003 Implementation Specific Behavior and C++
2011 Implementation Specific Behavior. This section only documents behaviour which is new in the 2017 standard.
23.6.5 [optional.bad_optional_access] what() returns "bad optional access".
23.7.3 [variant.variant] Whether variant supports over-aligned types should be documented here.
23.7.10 [variant.bad.access] what() returns "Unexpected index".

The GNU C++ Library Manual

Library Feature
constexpr std::
hardware_{construc
tive,destructive}_
interference_size
Core Issue 1776:
Replacement of class
objects containing reference
members

9 / 399

Proposal

Status

SD-6 Feature Test

P0154R1

No

__cpp_lib_hardware
_interference_size
>=201603

P0137R1

7.1

__cpp_lib_launder
>=201606

Wording for std::uncau
ght_exceptions

N4259

6.1

Variant: a type-safe union
for C++17

P0088R3

7.1

Library Fundamentals V1
TS Components:
optional

P0220R1

7.1

Library Fundamentals V1
TS Components: any

P0220R1

7.1

Library Fundamentals V1
TS Components:
string_view

P0220R1

7.1

Library Fundamentals V1
TS Components:
memory_resource

P0220R1

No

P0220R1

7.1

P0220R1

7.1

P0220R1

7.1

P0220R1

7.1

P0007R1

7.1

N4387

6.1

P0209R2

7.1

Library Fundamentals V1
TS Components: apply
Library Fundamentals V1
TS Components:
shared_ptr
Library Fundamentals V1
TS Components: Searchers
Library Fundamentals V1
TS Components: Sampling
Constant View: A proposal
for a std::as_const
helper function template
Improving pair and tuple
make_from_tuple:
apply for construction
Removing auto_ptr,
random_shuffle(),
And Old 
Stuff
Deprecating Vestigial
Library Parts in C++17
Making std::
owner_less more
flexible
std::addressof should
be constexpr

N4190

__cpp_lib_uncaught
_exceptions >=
201411
__has_include(),
__cpp_lib_variant
>=201603 (since 7.3, see
Note 1)
__has_include(),
__cpp_lib_optional
>=201603 (since 7.3, see
Note 1)
__has_include(), __cpp_lib_any
>=201603 (since 7.3, see
Note 1)
__has_include(), __cpp_li
b_string_view >=
201603 (since 7.3, see
Note 1)
__has_include(),
__cpp_lib_memory_r
esource >=201603
__cpp_lib_apply >=
201603
__cpp_lib_shared_p
tr_arrays >=201603
__cpp_lib_boyer_mo
ore_searcher >=
201603
__cpp_lib_sample
>=201603
__cpp_lib_as_const
>=201510
N/A
__cpp_lib_make_fr
om_tuple >=201606

No (kept for backwards
compatibility)

P0174R2

No

P0074R0

7.1

LWG2296

7.1

__cpp_lib_transpa
rent_operators >=
201510
__cpp_lib_address
of_constexpr >=
201603

The GNU C++ Library Manual

Paper
N4076
N4273
N4061
N4066
N4282
N4388
N4391
N4502
N4519
N4521
P0013R1

10 / 399

Title
A generalized callable
negator
Uniform Container Erasure
Greatest Common Divisor
and Least Common
Multiple
Delimited iterators
The World’s Dumbest
Smart Pointer
Const-Propagating Wrapper
make_array, revision 4
Support for the C++
Detection Idiom, V2
Source-Code Information
Capture
Merge Fundamentals V1
into V2
Logical Operator Type
Traits (revision 1)

Status

Comments

Y

Library Fundamentals 2 TS

Y

Library Fundamentals 2 TS

Y

Library Fundamentals 2 TS

Y

Library Fundamentals 2 TS

Y

Library Fundamentals 2 TS

Y
Y

Library Fundamentals 2 TS
Library Fundamentals 2 TS

Y

Library Fundamentals 2 TS

Y

Library Fundamentals 2 TS

N

Library Fundamentals 2 TS

Y

Library Fundamentals 2 TS

Table 1.6: C++ Technical Specifications Implementation Status
23.12.5.2 [memory.resource.pool.options] The limits for maximum number of blocks and largest allocation size supported by
pool_options should be documented here.
23.12.6.1 [memory.resource.monotonic.buffer.ctor] The default next_buffer_size and growth factor should be documented
here.
23.15.4.3 [meta.unary.prop] The predicate condition for has_unique_object_representations is true for all scalar
types except floating point types.
23.19.3 [execpol.type], 28.4.3 [algorithms.parallel.exec] There are no implementation-defined execution policies.
24.4.2 [string.view.template] basic_string_view::iterator is C* and basic_string_view::
const_iterator is const C*.
28.4.3 [algorithms.parallel.exec] Threads of execution created by std::thread provide concurrent forward progress guarantees, so threads of execution implicitly created by the library will provide parallel forward progress guarantees.
29.4.1 [cfenv.syn] The effects of the  functions depends on whether the FENV_ACCESS pragma is supported, and on
the C library that provides the header.
29.6.9 [c.math.rand] Whether the rand function may introduce data races depends on the target C library that provides the
function.
29.9.5 [sf.cmath] The effect of calling the mathematical special functions with large inputs should be documented here.
30.10.2.1 [fs.conform.9945] The behavior of the filesystem library implementation will depend on the target operating system.
Some features will not be not supported on some targets.
30.10.5 [fs.filesystem.syn] The clock used for file times is std::chrono::system_clock.
30.10.7.1 [fs.path.generic] dot-dot in the root-directory refers to the root-directory itself.

1.1.5

C++ TR1

This table is based on the table of contents of ISO/IEC DTR 19768 Doc No: N1836=05-0096 Date: 2005-06-24 Draft Technical
Report on C++ Library Extensions
In this implementation the header names are prefixed by tr1/, for instance , , and so
on.
This page describes the TR1 support in the GCC 7 series.

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Section
2
2.1
2.1.1
2.1.2
2.1.2.1
2.1.2.2
2.1.2.3
2.1.2.4
2.1.2.5
2.2
2.2.1
2.2.2
2.2.3
2.2.3.1
2.2.3.2
2.2.3.3
2.2.3.4
2.2.3.5
2.2.3.6
2.2.3.7
2.2.3.8
2.2.3.9
2.2.3.10
2.2.4
2.2.4.1
2.2.4.2
2.2.4.3
2.2.4.4
2.2.4.5
2.2.4.6
2.2.4.7
2.2.5
3
3.1
3.2
3.3
3.4
3.5
3.6
3.6.1
3.6.2
3.6.3
3.6.4
3.7

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Description
General Utilities
Reference wrappers
Additions to header
 synopsis
Class template
reference_wrapper
reference_wrapper
construct/copy/destroy
reference_wrapper
assignment
reference_wrapper
access
reference_wrapper
invocation
reference_wrapper
helper functions
Smart pointers
Additions to header
 synopsis
Class bad_weak_ptr

Status

Y

Y
Y
Y
Y
Y

Y
Y
Uses code from
boost::shared_ptr.

Class template
shared_ptr
shared_ptr constructors
shared_ptr destructor
shared_ptr assignment
shared_ptr modifiers
shared_ptr observers
shared_ptr comparison
shared_ptr I/O
shared_ptr specialized
algorithms
shared_ptr casts
get_deleter
Class template weak_ptr
weak_ptr constructors
weak_ptr destructor
weak_ptr assignment
weak_ptr modifiers
weak_ptr observers
weak_ptr comparison
weak_ptr specialized
algorithms
Class template enable_s
hared_from_this
Function Objects
Definitions
Additions to

synopsis
Requirements
Function return types
Function template mem_fn
Function object binders
Class template
is_bind_expression
Class template
is_placeholder
Function template bind
Placeholders
Polymorphic function
wrappers

Comments

Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y

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Implementation Specific Behavior

For behaviour which is specified by the 1998 and 2003 standards, see C++ 1998/2003 Implementation Specific Behavior. This
section documents behaviour which is required by TR1.
3.6.4 [tr.func.bind.place]/1 There are 29 placeholders defined and the placeholder types are Assignable.

1.1.6

C++ TR 24733

This table is based on the table of contents of ISO/IEC TR 24733 Date: 2009-08-28 Extension for the programming language
C++ to support decimal floating-point arithmetic
This page describes the TR 24733 support in the GCC 7 series.

1.1.7

C++ IS 29124

This table is based on the table of contents of ISO/IEC FDIS 29124 Doc No: N3060 Date: 2010-03-06 Extensions to the C++
Library to support mathematical special functions
Complete support for IS 29124 is in GCC 6.1 and later releases, when using at least C++11 (for older releases or C++98/C++03
use TR1 instead). For C++11 and C++14 the additions to the library are not declared by their respective headers unless __STD
CPP_WANT_MATH_SPEC_FUNCS__ is defined as a macro that expands to a non-zero integer constant. For C++17 the special
functions are always declared (since GCC 7.1).
When the special functions are declared the macro __STDCPP_MATH_SPEC_FUNCS__ is defined to 201003L.
In addition to the special functions defined in IS 29124, for non-strict modes (i.e. -std=gnu++NN modes) the hypergeometric
functions and confluent hypergeometric functions from TR1 are also provided, defined in namespace __gnu_cxx.
1.1.7.1

Implementation Specific Behavior

For behaviour which is specified by the 2011 standard, see C++ 2011 Implementation Specific Behavior. This section documents
behaviour which is required by IS 29124.
7.2 [macro.user]/3 /4 The functions declared in Clause 8 are only declared when __STDCPP_WANT_MATH_SPEC_FUNCS__
==1 (or in C++17 mode, for GCC 7.1 and later).
8.1.1 [sf.cmath.Lnm]/1 The effect of calling these functions with n >=128 or m >=128 should be described here.
8.1.2 [sf.cmath.Plm]/3 The effect of calling these functions with l >=128 should be described here.
8.1.3 [sf.cmath.I]/3 The effect of calling these functions with nu >=128 should be described here.
8.1.8 [sf.cmath.J]/3 The effect of calling these functions with nu >=128 should be described here.
8.1.9 [sf.cmath.K]/3 The effect of calling these functions with nu >=128 should be described here.
8.1.10 [sf.cmath.N]/3 The effect of calling these functions with nu >=128 should be described here.
8.1.15 [sf.cmath.Hn]/3 The effect of calling these functions with n >=128 should be described here.
8.1.16 [sf.cmath.Ln]/3 The effect of calling these functions with n >=128 should be described here.
8.1.17 [sf.cmath.Pl]/3 The effect of calling these functions with l >=128 should be described here.
8.1.19 [sf.cmath.j]/3 The effect of calling these functions with n >=128 should be described here.
8.1.20 [sf.cmath.Ylm]/3 The effect of calling these functions with l >=128 should be described here.
8.1.21 [sf.cmath.n]/3 The effect of calling these functions with n >=128 should be described here.

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0
1
2
3
3.1
3.2

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Description
Introduction
Normative references
Conventions
Decimal floating-point types
Characteristics of decimal
floating-point types
Decimal Types

Status

3.2.1

Class decimal synopsis

Partial

3.2.2

Class decimal32

Partial

3.2.3

Class decimal64

Partial

3.2.4

Class decimal128

Partial

3.2.5
3.2.6
3.2.7
3.2.8
3.2.9
3.2.10
3.2.11
3.3
3.4
3.4.2
3.4.3
3.4.4
3.4.5
3.4.6
3.4.7
3.4.8
3.5
3.6
3.7
3.8
3.9
3.10

Initialization from
coefficient and exponent
Conversion to generic
floating-point type
Unary arithmetic operators
Binary arithmetic operators
Comparison operators
Formatted input
Formatted output
Additions to header
limits
Headers cfloat and
float.h
Additions to header
cfloat synopsis
Additions to header
float.h synopsis
Maximum finite value
Epsilon
Minimum positive normal
value
Minimum positive
subnormal value
Evaluation format
Additions to cfenv and
fenv.h
Additions to cmath and
math.h
Additions to cstdio and
stdio.h
Additions to cstdlib and
stdlib.h
Additions to cwchar and
wchar.h
Facets

Y
Y
Y
Y
Y
N
N
N

Y
N
Y
Y
Y
Y
Y
Outside the scope of GCC
Outside the scope of GCC
Outside the scope of GCC
Outside the scope of GCC
Outside the scope of GCC
N

Comments

Missing declarations for
formatted input/output;
non-conforming extension
for functions converting to
integral type
Missing 3.2.2.5 conversion
to integral type; conforming
extension for conversion
from scalar decimal
floating-point
Missing 3.2.3.5 conversion
to integral type; conforming
extension for conversion
from scalar decimal
floating-point
Missing 3.2.4.5 conversion
to integral type; conforming
extension for conversion
from scalar decimal
floating-point

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Section

Description

Status

7

Macro names

Partial

8
8.1
8.1.1
8.1.2
8.1.3
8.1.4
8.1.5
8.1.6
8.1.7
8.1.8
8.1.9
8.1.10
8.1.11
8.1.12
8.1.13
8.1.14
8.1.15
8.1.16
8.1.17
8.1.18
8.1.19
8.1.20
8.1.21
8.2

Mathematical special
functions
Additions to header
 synopsis
associated Laguerre
polynomials
associated Legendre
functions
beta function
(complete) elliptic integral
of the first kind
(complete) elliptic integral
of the second kind
(complete) elliptic integral
of the third kind
regular modified cylindrical
Bessel functions
cylindrical Bessel functions
(of the first kind)
irregular modified
cylindrical Bessel functions
cylindrical Neumann
functions
(incomplete) elliptic
integral of the first kind
(incomplete) elliptic
integral of the second kind
(incomplete) elliptic
integral of the third kind
exponential integral
Hermite polynomials
Laguerre polynomials
Legendre polynomials
Riemann zeta function
spherical Bessel functions
(of the first kind)
spherical associated
Legendre functions
spherical Neumann
functions
Additions to header


Comments
No diagnostic for
inconsistent definitions of
__STDCPP_WANT_MATH
_SPEC_FUNCS__

Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y

8.3

The header 

Partial

8.4

The header 

N

Table 1.9: C++ Special Functions Implementation Status

Conflicts with C++ 2011
requirements.
Conflicts with C++ 2011
requirements.

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License

There are two licenses affecting GNU libstdc++: one for the code, and one for the documentation.
There is a license section in the FAQ regarding common questions. If you have more questions, ask the FSF or the gcc mailing
list.

1.2.1

The Code: GPL

The source code is distributed under the GNU General Public License version 3, with the addition under section 7 of an exception
described in the “GCC Runtime Library Exception, version 3.1” as follows (or see the file COPYING.RUNTIME):
GCC RUNTIME LIBRARY EXCEPTION
Version 3.1, 31 March 2009
Copyright (C) 2009 Free Software Foundation, Inc.
Everyone is permitted to copy and distribute verbatim copies of this
license document, but changing it is not allowed.
This GCC Runtime Library Exception ("Exception") is an additional
permission under section 7 of the GNU General Public License, version
3 ("GPLv3"). It applies to a given file (the "Runtime Library") that
bears a notice placed by the copyright holder of the file stating that
the file is governed by GPLv3 along with this Exception.
When you use GCC to compile a program, GCC may combine portions of
certain GCC header files and runtime libraries with the compiled
program. The purpose of this Exception is to allow compilation of
non-GPL (including proprietary) programs to use, in this way, the
header files and runtime libraries covered by this Exception.
0. Definitions.
A file is an "Independent Module" if it either requires the Runtime
Library for execution after a Compilation Process, or makes use of an
interface provided by the Runtime Library, but is not otherwise based
on the Runtime Library.
"GCC" means a version of the GNU Compiler Collection, with or without
modifications, governed by version 3 (or a specified later version) of
the GNU General Public License (GPL) with the option of using any
subsequent versions published by the FSF.
"GPL-compatible Software" is software whose conditions of propagation,
modification and use would permit combination with GCC in accord with
the license of GCC.
"Target Code" refers to output from any compiler for a real or virtual
target processor architecture, in executable form or suitable for
input to an assembler, loader, linker and/or execution
phase. Notwithstanding that, Target Code does not include data in any
format that is used as a compiler intermediate representation, or used
for producing a compiler intermediate representation.

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The "Compilation Process" transforms code entirely represented in
non-intermediate languages designed for human-written code, and/or in
Java Virtual Machine byte code, into Target Code. Thus, for example,
use of source code generators and preprocessors need not be considered
part of the Compilation Process, since the Compilation Process can be
understood as starting with the output of the generators or
preprocessors.
A Compilation Process is "Eligible" if it is done using GCC, alone or
with other GPL-compatible software, or if it is done without using any
work based on GCC. For example, using non-GPL-compatible Software to
optimize any GCC intermediate representations would not qualify as an
Eligible Compilation Process.
1. Grant of Additional Permission.
You have permission to propagate a work of Target Code formed by
combining the Runtime Library with Independent Modules, even if such
propagation would otherwise violate the terms of GPLv3, provided that
all Target Code was generated by Eligible Compilation Processes. You
may then convey such a combination under terms of your choice,
consistent with the licensing of the Independent Modules.
2. No Weakening of GCC Copyleft.
The availability of this Exception does not imply any general
presumption that third-party software is unaffected by the copyleft
requirements of the license of GCC.
Hopefully that text is self-explanatory. If it isn’t, you need to speak to your lawyer, or the Free Software Foundation.

1.2.2

The Documentation: GPL, FDL

The documentation shipped with the library and made available over the web, excluding the pages generated from source comments, are copyrighted by the Free Software Foundation, and placed under the GNU Free Documentation License version 1.3.
There are no Front-Cover Texts, no Back-Cover Texts, and no Invariant Sections.
For documentation generated by doxygen or other automated tools via processing source code comments and markup, the original
source code license applies to the generated files. Thus, the doxygen documents are licensed GPL.
If you plan on making copies of the documentation, please let us know. We can probably offer suggestions.

1.3
1.3.1

Bugs
Implementation Bugs

Information on known bugs, details on efforts to fix them, and fixed bugs are all available as part of the GCC bug tracking system,
with the category set to libstdc++.

1.3.2

Standard Bugs

Everybody’s got issues. Even the C++ Standard Library.
The Library Working Group, or LWG, is the ISO subcommittee responsible for making changes to the library. They periodically
publish an Issues List containing problems and possible solutions. As they reach a consensus on proposed solutions, we often
incorporate the solution.

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Here are the issues which have resulted in code changes to the library. The links are to the specific defect reports from a partial
copy of the Issues List. You can read the full version online at the ISO C++ Committee homepage.
If a DR is not listed here, we may simply not have gotten to it yet; feel free to submit a patch. Search the include/bits and src
directories for appearances of _GLIBCXX_RESOLVE_LIB_DEFECTS for examples of style. Note that we usually do not make
changes to the code until an issue has reached DR status.
5: string::compare specification questionable This should be two overloaded functions rather than a single function.
17: Bad bool parsing Apparently extracting Boolean values was messed up...
19: "Noconv" definition too vague If codecvt::do_in returns noconv there are no changes to the values in [to, to_
limit).
22: Member open vs flags Re-opening a file stream does not clear the state flags.
23: Num_get overflow result Implement the proposed resolution.
25: String operator<< uses width() value wrong Padding issues.
48: Use of non-existent exception constructor An instance of ios_base::failure is constructed instead.
49: Underspecification of ios_base::sync_with_stdio The return type is the previous state of synchronization.
50: Copy constructor and assignment operator of ios_base These members functions are declared private and are thus inaccessible. Specifying the correct semantics of "copying stream state" was deemed too complicated.
60: What is a formatted input function? This DR made many widespread changes to basic_istream and basic_ostr
eam all of which have been implemented.
63: Exception-handling policy for unformatted output Make the policy consistent with that of formatted input, unformatted
input, and formatted output.
68: Extractors for char* should store null at end And they do now. An editing glitch in the last item in the list of [27.6.1.2.3]/7.
74: Garbled text for codecvt::do_max_length The text of the standard was gibberish. Typos gone rampant.
75: Contradiction in codecvt::length’s argument types Change the first parameter to stateT& and implement the new effects
paragraph.
83: string::npos vs. string::max_size() Safety checks on the size of the string should test against max_size() rather than
npos.
90: Incorrect description of operator>> for strings The effect contain isspace(c,getloc()) which must be replaced by
isspace(c,is.getloc()).
91: Description of operator>> and getline() for string<> might cause endless loop They behave as a formatted input function
and as an unformatted input function, respectively (except that getline is not required to set gcount).
103: set::iterator is required to be modifiable, but this allows modification of keys. For associative containers where the value
type is the same as the key type, both iterator and const_iterator are constant iterators.
109: Missing binders for non-const sequence elements The binder1st and binder2nd didn’t have an operator()
taking a non-const parameter.
110: istreambuf_iterator::equal not const This was not a const member function. Note that the DR says to replace the function
with a const one; we have instead provided an overloaded version with identical contents.
117: basic_ostream uses nonexistent num_put member functions num_put::put() was overloaded on the wrong types.
118: basic_istream uses nonexistent num_get member functions Same as 117, but for num_get::get().
129: Need error indication from seekp() and seekg() These functions set failbit on error now.
130: Return type of container::erase(iterator) differs for associative containers Make member erase return iterator for set,
multiset, map, multimap.

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136: seekp, seekg setting wrong streams? seekp should only set the output stream, and seekg should only set the input
stream.
167: Improper use of traits_type::length() op<< with a const char* was calculating an incorrect number of characters to
write.
169: Bad efficiency of overflow() mandated Grow efficiently the internal array object.
171: Strange seekpos() semantics due to joint position Quite complex to summarize...
181: make_pair() unintended behavior This function used to take its arguments as reference-to-const, now it copies them (pass
by value).
195: Should basic_istream::sentry’s constructor ever set eofbit? Yes, it can, specifically if EOF is reached while skipping
whitespace.
211: operator>>(istream&, string&) doesn’t set failbit If nothing is extracted into the string, op>> now sets failbit (which
can cause an exception, etc., etc.).
214: set::find() missing const overload Both set and multiset were missing overloaded find, lower_bound, upper_bound,
and equal_range functions for const instances.
231: Precision in iostream? For conversion from a floating-point type, str.precision() is specified in the conversion
specification.
233: Insertion hints in associative containers Implement N1780, first check before then check after, insert as close to hint as
possible.
235: No specification of default ctor for reverse_iterator The declaration of reverse_iterator lists a default constructor.
However, no specification is given what this constructor should do.
241: Does unique_copy() require CopyConstructible and Assignable? Add a helper for forward_iterator/output_iterator, fix
the existing one for input_iterator/output_iterator to not rely on Assignability.
243: get and getline when sentry reports failure Store a null character only if the character array has a non-zero size.
251: basic_stringbuf missing allocator_type This nested typedef was originally not specified.
253: valarray helper functions are almost entirely useless Make the copy constructor and copy-assignment operator declarations public in gslice_array, indirect_array, mask_array, slice_array; provide definitions.
265: std::pair::pair() effects overly restrictive The default ctor would build its members from copies of temporaries; now it
simply uses their respective default ctors.
266: bad_exception::~bad_exception() missing Effects clause The bad_* classes no longer have destructors (they are trivial),
since no description of them was ever given.
271: basic_iostream missing typedefs The typedefs it inherits from its base classes can’t be used, since (for example) basic_
iostream::traits_type is ambiguous.
275: Wrong type in num_get::get() overloads Similar to 118.
280: Comparison of reverse_iterator to const reverse_iterator Add global functions with two template parameters. (NB: not
added for now a templated assignment operator)
292: Effects of a.copyfmt (a) If (this ==&rhs) do nothing.
300: List::merge() specification incomplete If (this ==&x) do nothing.
303: Bitset input operator underspecified Basically, compare the input character to is.widen(0) and is.widen(1).
305: Default behavior of codecvt::length() Do not specify what codecvt::do_length must return.
328: Bad sprintf format modifier in money_put<>::do_put() Change the format string to "%.0Lf".

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365: Lack of const-qualification in clause 27 Add const overloads of is_open.
387: std::complex over-encapsulated Add the real(T) and imag(T) members; in C++11 mode, also adjust the existing
real() and imag() members and free functions.
389: Const overload of valarray::operator[] returns by value Change it to return a const T&.
396: what are characters zero and one Implement the proposed resolution.
402: Wrong new expression in [some_]allocator::construct Replace "new" with "::new".
408: Is vector > forbidden?

Tweak the debug-mode checks in _Safe_iterator.

409: Closing an fstream should clear the error state Have open clear the error flags.
431: Swapping containers with unequal allocators Implement Option 3, as per N1599.
432: stringbuf::overflow() makes only one write position available Implement the resolution, beyond DR 169.
434: bitset::to_string() hard to use Add three overloads, taking fewer template arguments.
438: Ambiguity in the "do the right thing" clause Implement the resolution, basically cast less.
445: iterator_traits::reference unspecified for some iterator categories Change istreambuf_iterator::reference in
C++11 mode.
453: basic_stringbuf::seekoff need not always fail for an empty stream Don’t fail if the next pointer is null and newoff is zero.
455: cerr::tie() and wcerr::tie() are overspecified Initialize cerr tied to cout and wcerr tied to wcout.
464: Suggestion for new member functions in standard containers Add data() to std::vector and at(const key_
type&) to std::map.
467: char_traits::lt(), compare(), and memcmp() Change lt.
508: Bad parameters for ranlux64_base_01 Fix the parameters.
512: Seeding subtract_with_carry_01 from a single unsigned long Construct a linear_congruential engine and seed
with it.
526: Is it undefined if a function in the standard changes in parameters? Use &value.
538: 241 again: Does unique_copy() require CopyConstructible and Assignable? In case of input_iterator/output_iterator rely
on Assignability of input_iterator’ value_type.
539: partial_sum and adjacent_difference should mention requirements We were almost doing the right thing, just use std::move
in adjacent_difference.
541: shared_ptr template assignment and void Add an auto_ptr specialization.
543: valarray slice default constructor Follow the straightforward proposed resolution.
550: What should the return type of pow(float,int) be? In C++11 mode, remove the pow(float,int), etc., signatures.
586: string inserter not a formatted function Change it to be a formatted output function (i.e. catch exceptions).
596: 27.8.1.3 Table 112 omits "a+" and "a+b" modes Add the missing modes to fopen_mode.
630: arrays of valarray Implement the simple resolution.
660: Missing bitwise operations Add the missing operations.
691: const_local_iterator cbegin, cend missing from TR1 In C++11 mode add cbegin(size_type) and cend(size_type) to the
unordered containers.
693: std::bitset::all() missing Add it, consistently with the discussion.

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695: ctype::classic_table() not accessible Make the member functions table and classic_table public.
696: istream::operator>>(int&) broken Implement the straightforward resolution.
761: unordered_map needs an at() member function In C++11 mode, add at() and at() const.
775: Tuple indexing should be unsigned? Implement the int -> size_t replacements.
776: Undescribed assign function of std::array In C++11 mode, remove assign, add fill.
781: std::complex should add missing C99 functions In C++11 mode, add std::proj.
809: std::swap should be overloaded for array types Add the overload.
853: to_string needs updating with zero and one Update / add the signatures.
865: More algorithms that throw away information The traditional HP / SGI return type and value is blessed by the resolution
of the DR.
1339: uninitialized_fill_n should return the end of its range Return the end of the filled range.
2021: Further incorrect uses of result_of Correctly decay types in signature of std::async.
2049: is_destructible underspecified Handle non-object types.
2056: future_errc enums start with value 0 (invalid value for broken_promise) Reorder enumerators.
2059: C++0x ambiguity problem with map::erase Add additional overloads.
2062: 2062. Effect contradictions w/o no-throw guarantee of std::function swaps Add noexcept to swap functions.
2063: Contradictory requirements for string move assignment Respect propagation trait for move assignment.
2064: More noexcept issues in basic_string Add noexcept to the comparison operators.
2067: packaged_task should have deleted copy c’tor with const parameter Fix signatures.
2101: Some transformation types can produce impossible types Use the referenceable type concept.
2106: move_iterator wrapping iterators returning prvalues Change the reference type.
2108: No way to identify allocator types that always compare equal Define and use is_always_equal even for C++11.
2118: unique_ptr for array does not support cv qualification conversion of actual argument Adjust constraints to allow safe
conversions.
2127: Move-construction with raw_storage_iterator Add assignment operator taking an rvalue.
2132: std::function ambiguity Constrain the constructor to only accept callable types.
2141: common_type trait produces reference types Use decay for the result type.
2144: Missing noexcept specification in type_index Add noexcept
2145: error_category default constructor Declare a public constexpr constructor.
2162: allocator_traits::max_size missing noexcept Add noexcept.
2187: vector is missing emplace and emplace_back member functions Add emplace and emplace_back
member functions.
2192: Validity and return type of std::abs(0u) is unclear Move all declarations to a common header and remove the generic
abs which accepted unsigned arguments.
2196: Specification of is_*[copy/move]_[constructible/assignable] unclear for non-referencable types Use
the referenceable type concept.

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2212: tuple_size for const pair request  header The tuple_size and tuple_element partial specializations are defined in  which is included by .
2296: std::addressof should be constexpr Use __builtin_addressof and add constexpr to addressof for
C++17 and later.
2313: tuple_size should always derive from integral_constant Update definitions of the partial specializations for const and volatile types.
2328: Rvalue stream extraction should use perfect forwarding Use perfect forwarding for right operand.
2329: regex_match()/regex_search() with match_results should forbid temporary strings Add deleted overloads
for rvalue strings.
2332: regex_iterator/regex_token_iterator should forbid temporary regexes Add deleted constructors.
2332: Unnecessary copying when inserting into maps with braced-init syntax Add overloads of insert taking value_ty
pe&& rvalues.
2399: shared_ptr’s constructor from unique_ptr should be constrained Constrain the constructor to require convertibility.
2400: shared_ptr’s get_deleter() should use addressof() Use addressof.
2401: std::function needs more noexcept Add noexcept to the assignment and comparisons.
2407: packaged_task(allocator_arg_t, const Allocator&, F&&) should neither be constrained nor explicit
Remove explicit from the constructor.
2415: Inconsistency between unique_ptr and shared_ptr Create empty an shared_ptr from an empty unique_
ptr.
2418: apply does not work with member pointers Use mem_fn for member pointers.
2440: seed_seq::size() should be noexcept Add noexcept.
2441: Exact-width atomic typedefs should be provided Define the typedefs.
2442: call_once() shouldn’t DECAY_COPY() Remove indirection through call wrapper that made copies of arguments
and forward arguments straight to std::invoke.
2454: Add raw_storage_iterator::base() member

Add the base() member function.

2455: Allocator default construction should be allowed to throw Make noexcept specifications conditional.
2458: N3778 and new library deallocation signatures Remove unused overloads.
2459: std::polar should require a non-negative rho Add debug mode assertion.
2466: allocator_traits::max_size() default behavior is incorrect

Divide by the object type.

2484: rethrow_if_nested() is doubly unimplementable Avoid using dynamic_cast when it would be ill-formed.
2583: There is no way to supply an allocator for basic_string(str, pos)
2684: priority_queue lacking comparator typedef

Add new constructor

Define the value_compare typedef.

2770: tuple_size specialization is not SFINAE compatible and breaks decomposition declarations Safely detect tuple_size::value and only use it if valid.
2781: Contradictory requirements for std::function and std::reference_wrapper
reference_wrapper arguments and store them directly as the target object.
2802: Add noexcept to several shared_ptr related functions Add noexcept.
2873: shared_ptr constructor requirements for a deleter Use rvalues for deleters.
2942: LWG 2873’s resolution missed weak_ptr::owner_before

Add noexcept.

Remove special handling for

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Chapter 2

Setup
To transform libstdc++ sources into installed include files and properly built binaries useful for linking to other software is a
multi-step process. Steps include getting the sources, configuring and building the sources, testing, and installation.
The general outline of commands is something like:
get gcc sources
extract into gccsrcdir
mkdir gccbuilddir
cd gccbuilddir
gccsrcdir/configure --prefix=destdir --other-opts...
make
make check
make install

Each step is described in more detail in the following sections.

2.1

Prerequisites

Because libstdc++ is part of GCC, the primary source for installation instructions is the GCC install page. In particular, list of
prerequisite software needed to build the library starts with those requirements. The same pages also list the tools you will need
if you wish to modify the source.
Additional data is given here only where it applies to libstdc++.
As of GCC 4.0.1 the minimum version of binutils required to build libstdc++ is 2.15.90.0.1.1. Older releases of libstdc++
do not require such a recent version, but to take full advantage of useful space-saving features and bug-fixes you should use
a recent binutils whenever possible. The configure process will automatically detect and use these features if the underlying
support is present.
To generate the API documentation from the sources you will need Doxygen, see Documentation Hacking in the appendix for
full details.
Finally, a few system-specific requirements:
linux If GCC 3.1.0 or later on is being used on GNU/Linux, an attempt will be made to use "C" library functionality necessary
for C++ named locale support. For GCC 4.6.0 and later, this means that glibc 2.3 or later is required.
If the ’gnu’ locale model is being used, the following locales are used and tested in the libstdc++ testsuites. The first
column is the name of the locale, the second is the character set it is expected to use.
de_DE
de_DE@euro
en_GB

ISO-8859-1
ISO-8859-15
ISO-8859-1

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en_HK
en_PH
en_US
en_US.ISO-8859-1
en_US.ISO-8859-15
en_US.UTF-8
es_ES
es_MX
fr_FR
fr_FR@euro
is_IS
it_IT
ja_JP.eucjp
ru_RU.ISO-8859-5
ru_RU.UTF-8
se_NO.UTF-8
ta_IN
zh_TW

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ISO-8859-1
ISO-8859-1
ISO-8859-1
ISO-8859-1
ISO-8859-15
UTF-8
ISO-8859-1
ISO-8859-1
ISO-8859-1
ISO-8859-15
UTF-8
ISO-8859-1
EUC-JP
ISO-8859-5
UTF-8
UTF-8
UTF-8
BIG5

Failure to have installed the underlying "C" library locale information for any of the above regions means that the corresponding C++ named locale will not work: because of this, the libstdc++ testsuite will skip named locale tests which
need missing information. If this isn’t an issue, don’t worry about it. If a named locale is needed, the underlying locale
information must be installed. Note that rebuilding libstdc++ after "C" locales are installed is not necessary.
To install support for locales, do only one of the following:
• install all locales
• install just the necessary locales
– with Debian GNU/Linux:
Add the above list, as shown, to the file /etc/locale.gen
run /usr/sbin/locale-gen
– on most Unix-like operating systems:
localedef -i de_DE -f ISO-8859-1 de_DE
(repeat for each entry in the above list)
– Instructions for other operating systems solicited.

2.2

Configure

When configuring libstdc++, you’ll have to configure the entire gccsrcdir directory. Consider using the toplevel gcc configuration
option --enable-languages=c++, which saves time by only building the C++ toolchain.
Here are all of the configure options specific to libstdc++. Keep in mind that they all have opposite forms as well (enable/disable
and with/without). The defaults are for the current development sources, which may be different than those for released versions.
The canonical way to find out the configure options that are available for a given set of libstdc++ sources is to go to the source
directory and then type: ./configure --help.
--enable-multilib[default] This is part of the generic multilib support for building cross compilers. As such, targets like
"powerpc-elf" will have libstdc++ built many different ways: "-msoft-float" and not, etc. A different libstdc++ will be built
for each of the different multilib versions. This option is on by default.
--enable-version-specific-runtime-libs Specify that run-time libraries should be installed in the compilerspecific subdirectory (i.e., ${libdir}/gcc-lib/${target_alias}/${gcc_version}) instead of ${libd
ir}. This option is useful if you intend to use several versions of gcc in parallel. In addition, libstdc++’s include files will
be installed in ${libdir}/gcc-lib/${target_alias}/${gcc_version}/include/g++, unless you also
specify --with-gxx-include-dir=dirname during configuration.
--with-gxx-include-dir= Adds support for named libstdc++ include directory. For instance, the following puts all the libstdc++ headers into a directory called "4.4-20090404" instead of the usual "c++/(version)".

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--with-gxx-include-dir=/foo/H-x86-gcc-3-c-gxx-inc/include/4.4-20090404

--enable-cstdio This is an abbreviated form of ’--enable-cstdio=stdio’ (described next).
--enable-cstdio=OPTION Select a target-specific I/O package. At the moment, the only choice is to use ’stdio’, a generic
"C" abstraction. The default is ’stdio’. This option can change the library ABI.
--enable-clocale This is an abbreviated form of ’--enable-clocale=generic’ (described next).
--enable-clocale=OPTION Select a target-specific underlying locale package. The choices are ’ieee_1003.1-2001’ to
specify an X/Open, Standard Unix (IEEE Std. 1003.1-2001) model based on langinfo/iconv/catgets, ’gnu’ to specify a
model based on functionality from the GNU C library (langinfo/iconv/gettext) (from glibc, the GNU C library), ’generic’
to use a generic "C" abstraction which consists of "C" locale info, ’newlib’ to specify the Newlib C library model which
only differs from the ’generic’ model in the handling of ctype, or ’darwin’ which omits the wchar_t specializations needed
by the ’generic’ model.
If not explicitly specified, the configure process tries to guess the most suitable package from the choices above. The
default is ’generic’. On glibc-based systems of sufficient vintage (2.3 and newer), ’gnu’ is automatically selected. On
newlib-based systems (’--with_newlib=yes’) and OpenBSD, ’newlib’ is automatically selected. On Mac OS X
’darwin’ is automatically selected. This option can change the library ABI.
--enable-libstdcxx-allocator This is an abbreviated form of ’--enable-libstdcxx-allocator=auto’
(described next).
--enable-libstdcxx-allocator=OPTION Select a target-specific underlying std::allocator. The choices are ’new’
to specify a wrapper for new, ’malloc’ to specify a wrapper for malloc, ’mt’ for a fixed power of two allocator, ’pool’ for
the SGI pooled allocator or ’bitmap’ for a bitmap allocator. See this page for more information on allocator extensions.
This option can change the library ABI.
--enable-cheaders=OPTION This allows the user to define the approach taken for C header compatibility with C++. Options are c, c_std, and c_global. These correspond to the source directory’s include/c, include/c_std, and include/c_global,
and may also include include/c_compatibility. The default is ’c_global’.
--enable-threads This is an abbreviated form of ’--enable-threads=yes’ (described next).
--enable-threads=OPTION Select a threading library. A full description is given in the general compiler configuration
instructions. This option can change the library ABI.
--enable-libstdcxx-threads Enable C++11 threads support. If not explicitly specified, the configure process enables
it if possible. This option can change the library ABI.
--enable-libstdcxx-time This is an abbreviated form of ’--enable-libstdcxx-time=yes’(described next).
--enable-libstdcxx-time=OPTION Enables link-type checks for the availability of the clock_gettime clocks, used
in the implementation of [time.clock], and of the nanosleep and sched_yield functions, used in the implementation of
[thread.thread.this] of the 2011 ISO C++ standard. The choice OPTION=yes checks for the availability of the facilities in
libc and libposix4. In case it’s needed the latter is also linked to libstdc++ as part of the build process. OPTION=rt also
searches (and, if needed, links) librt. Note that the latter is not always desirable because, in glibc, for example, in turn it
triggers the linking of libpthread too, which activates locking, a large overhead for single-thread programs. OPTION=no
skips the tests completely. The default is OPTION=auto, which skips the checks and enables the features only for targets
known to support them.
--enable-libstdcxx-debug Build separate debug libraries in addition to what is normally built. By default, the debug
libraries are compiled with CXXFLAGS=’-g3 -O0 -fno-inline’ , are installed in ${libdir}/debug, and
have the same names and versioning information as the non-debug libraries. This option is off by default.
Note this make command, executed in the build directory, will do much the same thing, without the configuration difference
and without building everything twice: make CXXFLAGS=’-g3 -O0 -fno-inline’ all
--enable-libstdcxx-debug-flags=FLAGS This option is only valid when --enable-debug is also specified,
and applies to the debug builds only. With this option, you can pass a specific string of flags to the compiler to use when
building the debug versions of libstdc++. FLAGS is a quoted string of options, like

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--enable-libstdcxx-debug-flags=’-g3 -O1 -fno-inline’

--enable-cxx-flags=FLAGS With this option, you can pass a string of -f (functionality) flags to the compiler to use when
building libstdc++. This option can change the library ABI. FLAGS is a quoted string of options, like
--enable-cxx-flags=’-fvtable-gc -fomit-frame-pointer -ansi’

Note that the flags don’t necessarily have to all be -f flags, as shown, but usually those are the ones that will make sense
for experimentation and configure-time overriding.
The advantage of --enable-cxx-flags over setting CXXFLAGS in the ’make’ environment is that, if files are automatically
rebuilt, the same flags will be used when compiling those files as well, so that everything matches.
Fun flags to try might include combinations of
-fstrict-aliasing
-fno-exceptions
-ffunction-sections
-fvtable-gc

and opposite forms (-fno-) of the same. Tell us (the libstdc++ mailing list) if you discover more!
--enable-c99 The long long type was introduced in C99, along with many other functions for wide characters, and math
classification macros, etc. If enabled, all C99 functions not specified by the C++ standard will be put into namespace
__gnu_cxx, and then all these names will be injected into namespace std, so that C99 functions can be used "as if" they
were in the C++ standard (as they will eventually be in some future revision of the standard, without a doubt). By default,
C99 support is on, assuming the configure probes find all the necessary functions and bits necessary. This option can
change the library ABI.
--enable-wchar_t[default] Template specializations for the wchar_t type are required for wide character conversion support. Disabling wide character specializations may be expedient for initial porting efforts, but builds only a subset of what
is required by ISO, and is not recommended. By default, this option is on. This option can change the library ABI.
--enable-long-long The long long type was introduced in C99. It is provided as a GNU extension to C++98 in g++.
This flag builds support for "long long" into the library (specialized templates and the like for iostreams). This option is
on by default: if enabled, users will have to either use the new-style "C" headers by default (i.e.,  not )
or add appropriate compile-time flags to all compile lines to allow "C" visibility of this feature (on GNU/Linux, the flag
is -D_ISOC99_SOURCE, which is added automatically via CPLUSPLUS_CPP_SPEC’s addition of _GNU_SOURCE).
This option can change the library ABI.
--enable-fully-dynamic-string This option enables a special version of basic_string avoiding the optimization that
allocates empty objects in static memory. Mostly useful together with shared memory allocators, see PR libstdc++/16612
for details.
--enable-concept-checks This turns on additional compile-time checks for instantiated library templates, in the form
of specialized templates described in the Concept Checking section. They can help users discover when they break the
rules of the STL, before their programs run. These checks are based on C++03 rules and some of them are not compatible
with correct C++11 code.
--enable-symvers[=style] In 3.1 and later, tries to turn on symbol versioning in the shared library (if a shared library has been requested). Values for ’style’ that are currently supported are ’gnu’, ’gnu-versioned-namespace’, ’darwin’,
’darwin-export’, and ’sun’. Both gnu- options require that a recent version of the GNU linker be in use. Both darwin
options are equivalent. With no style given, the configure script will try to guess correct defaults for the host system, probe
to see if additional requirements are necessary and present for activation, and if so, will turn symbol versioning on. This
option can change the library ABI.
--enable-libstdcxx-visibility In 4.2 and later, enables or disables visibility attributes. If enabled (as by default),
and the compiler seems capable of passing the simple sanity checks thrown at it, adjusts items in namespace std, namespace
std::tr1, namespace std::tr2, and namespace __gnu_cxx to have visibility ("default") so that -fvisibility options
can be used without affecting the normal external-visibility of namespace std entities. Prior to 4.7 this option was spelled
--enable-visibility.

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--enable-libstdcxx-pch In 3.4 and later, tries to turn on the generation of stdc++.h.gch, a pre-compiled file including
all the standard C++ includes. If enabled (as by default), and the compiler seems capable of passing the simple sanity
checks thrown at it, try to build stdc++.h.gch as part of the make process. In addition, this generated file is used later on
(by appending --include bits/stdc++.h to CXXFLAGS) when running the testsuite.
--enable-extern-template[default] Use extern template to pre-instantiate all required specializations for certain types
defined in the standard libraries. These types include string and dependents like char_traits, the templatized IO
classes, allocator, and others. Disabling means that implicit template generation will be used when compiling these
types. By default, this option is on. This option can change the library ABI.
--disable-hosted-libstdcxx By default, a complete hosted C++ library is built. The C++ Standard also describes a
freestanding environment, in which only a minimal set of headers are provided. This option builds such an environment.
--disable-libstdcxx-verbose By default, the library is configured to write descriptive messages to standard error for
certain events such as calling a pure virtual function or the invocation of the standard terminate handler. Those messages
cause the library to depend on the demangler and standard I/O facilities, which might be undesirable in a low-memory
environment or when standard error is not available. This option disables those messages. This option does not change the
library ABI.
--disable-libstdcxx-dual-abi Disable support for the new, C++11-conforming implementations of std::str
ing, std::list etc. so that the library only provides definitions of types using the old ABI (see Dual ABI). This
option changes the library ABI.
--with-default-libstdcxx-abi=OPTION Set the default value for the _GLIBCXX_USE_CXX11_ABI macro (see
Macros). The default is OPTION=new which sets the macro to 1, use OPTION=gcc4-compatible to set it to 0. This
option does not change the library ABI.
--enable-vtable-verify[default] Use -fvtable-verify=std to compile the C++ runtime with instrumentation
for vtable verification. All virtual functions in the standard library will be verified at runtime. Types impacted include
locale and iostream, and others. Disabling means that the C++ runtime is compiled without support for vtable
verification. By default, this option is off.
--enable-libstdcxx-filesystem-ts[default] Build libstdc++fs.a as well as the usual libstdc++ and libsupc++
libraries. This is enabled by default on select POSIX targets where it is known to work and disabled otherwise.

2.3

Make

If you have never done this before, you should read the basic GCC Installation Instructions first. Read all of them. Twice.
Then type: make, and congratulations, you’ve started to build.

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Chapter 3

Using
3.1

Command Options

The set of features available in the GNU C++ library is shaped by several GCC Command Options. Options that impact libstdc++
are enumerated and detailed in the table below.
The standard library conforms to the dialect of C++ specified by the -std option passed to the compiler. By default, g++ is
equivalent to g++ -std=gnu++14 since GCC 6, and g++ -std=gnu++98 for older releases.
Option Flags
-std=c++98 or -std=c++03
-std=gnu++98 or -std=gnu++03
-std=c++11
-std=gnu++11
-std=c++14
-std=gnu++14
-fexceptions
-frtti
-pthread
-latomic
-lstdc++fs
-fopenmp

Description
Use the 1998 ISO C++ standard plus amendments.
As directly above, with GNU extensions.
Use the 2011 ISO C++ standard.
As directly above, with GNU extensions.
Use the 2014 ISO C++ standard.
As directly above, with GNU extensions.
See exception-free dialect
As above, but RTTI-free dialect.
For ISO C++11 , , , or
.
Linking to libatomic is required for some uses of ISO
C++11 .
Linking to libstdc++fs is required for use of the
Filesystem library extensions in
.
For parallel mode.
Table 3.1: C++ Command Options

3.2
3.2.1

Headers
Header Files

The C++ standard specifies the entire set of header files that must be available to all hosted implementations. Actually, the word
"files" is a misnomer, since the contents of the headers don’t necessarily have to be in any kind of external file. The only rule is
that when one #include’s a header, the contents of that header become available, no matter how.
That said, in practice files are used.

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There are two main types of include files: header files related to a specific version of the ISO C++ standard (called Standard
Headers), and all others (TR1, C++ ABI, and Extensions).
Two dialects of standard headers are supported, corresponding to the 1998 standard as updated for 2003, and the current 2011
standard.
C++98/03 include files. These are available in the default compilation mode, i.e. -std=c++98 or -std=gnu++98.
algorithm
fstream
iostream
locale
ostream
stdexcept
valarray

bitset
functional
istream
map
queue
streambuf
vector

complex
iomanip
iterator
memory
set
string

deque
ios
limits
new
sstream
utility

exception
iosfwd
list
numeric
stack
typeinfo

Table 3.2: C++ 1998 Library Headers
cassert
climits
cstdarg
ctime

cerrno
clocale
cstddef
cwchar

cctype
cmath
cstdio
cwctype

cfloat
csetjmp
cstdlib

ciso646
csignal
cstring

Table 3.3: C++ 1998 Library Headers for C Library Facilities
C++11 include files. These are only available in C++11 compilation mode, i.e. -std=c++11 or -std=gnu++11.
algorithm
condition_
variable

array

bitset

chrono

complex

deque

exception

forward_list

fstream

functional

future

iomanip

ios

iosfwd
list
new
ratio
stdexcept
tuple
utility

iostream
locale
numeric
regex
streambuf
type_traits
valarray

iterator
memory
queue
sstream
system_error
unordered_map

limits
mutex
random
stack
thread
unordered_set

initalizer_
list
istream
map
ostream
set
string
typeinfo
vector

Table 3.4: C++ 2011 Library Headers
In addition, TR1 includes as:
Decimal floating-point arithmetic is available if the C++ compiler supports scalar decimal floating-point types defined via __at
tribute__((mode(SD|DD|LD))).
Also included are files for the C++ ABI interface:
And a large variety of extensions.

3.2.2

Mixing Headers

A few simple rules.
First, mixing different dialects of the standard headers is not possible. It’s an all-or-nothing affair. Thus, code like

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cfloat
cmath
cstddef
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ccomplex
cinttypes
csetjmp
cstdint
ctime

cctype
ciso646
csignal
cstdlib
cuchar

cerrno
climits
cstdarg
cstdio
cwchar

cfenv
clocale
cstdbool
cstring
cwctype

Table 3.5: C++ 2011 Library Headers for C Library Facilities
tr1/array

tr1/complex

tr1/regex

tr1/tuple

tr1/memory
tr1/type_
traits

tr1/functional
tr1/unordered_
map

tr1/random
tr1/unordered_
set

tr1/utility
Table 3.6: C++ TR 1 Library Headers
tr1/ccomplex
tr1/climits
tr1/cstdlib

tr1/cfenv
tr1/cstdarg
tr1/ctgmath

tr1/cfloat
tr1/cstdbool
tr1/ctime

tr1/cmath
tr1/cstdint
tr1/cwchar

tr1/cinttypes
tr1/cstdio
tr1/cwctype

Table 3.7: C++ TR 1 Library Headers for C Library Facilities
decimal/decimal
Table 3.8: C++ TR 24733 Decimal Floating-Point Header
cxxabi.h

cxxabi_forced.h
Table 3.9: C++ ABI Headers
ext/array_
allocator.h

ext/bitmap_
allocator.h

ext/cast.h

ext/codecvt_
ext/
specializations.
concurrence.h
h

ext/debug_
allocator.h

ext/enc_
filebuf.h

ext/extptr_
allocator.h

ext/functional

ext/iterator

ext/malloc_
allocator.h

ext/memory

ext/new_
allocator.h

ext/numeric

ext/numeric_
traits.h

ext/pb_ds/
assoc_
container.h

ext/mt_
allocator.h
ext/pb_ds/
priority_
queue.h

ext/rb_tree

ext/rope

ext/slist

ext/throw_
allocator.h

ext/typelist.h

ext/type_
traits.h

ext/algorithm

ext/pod_char_
traits.h
ext/stdio_
filebuf.h
ext/vstring.h

ext/atomicity.
h

ext/pool_
allocator.h
ext/stdio_
sync_filebuf.h

Table 3.10: Extension Headers
debug/bitset
debug/string

debug/deque
debug/
unordered_map

debug/list
debug/
unordered_set

debug/map
debug/vector

Table 3.11: Extension Debug Headers

debug/set

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profile/deque
profile/unordered_
map

profile/list
profile/unordered_
set

profile/map
profile/vector

Table 3.12: Extension Profile Headers
parallel/algorithm

parallel/numeric
Table 3.13: Extension Parallel Headers

#include 
#include 

Implies C++11 mode. To use the entities in , the C++11 compilation mode must be used, which implies the C++11
functionality (and deprecations) in  will be present.
Second, the other headers can be included with either dialect of the standard headers, although features and types specific to
C++11 are still only enabled when in C++11 compilation mode. So, to use rvalue references with __gnu_cxx::vstring,
or to use the debug-mode versions of std::unordered_map, one must use the std=gnu++11 compiler flag. (Or std=
c++11, of course.)
A special case of the second rule is the mixing of TR1 and C++11 facilities. It is possible (although not especially prudent) to
include both the TR1 version and the C++11 version of header in the same translation unit:
#include 
#include 

Several parts of C++11 diverge quite substantially from TR1 predecessors.

3.2.3

The C Headers and namespace std

The standard specifies that if one includes the C-style header ( in this case), the symbols will be available in the global
namespace and perhaps in namespace std:: (but this is no longer a firm requirement.) On the other hand, including the
C++-style header () guarantees that the entities will be found in namespace std and perhaps in the global namespace.
Usage of C++-style headers is recommended, as then C-linkage names can be disambiguated by explicit qualification, such as by
std::abort. In addition, the C++-style headers can use function overloading to provide a simpler interface to certain families
of C-functions. For instance in , the function std::sin has overloads for all the builtin floating-point types. This
means that std::sin can be used uniformly, instead of a combination of std::sinf, std::sin, and std::sinl.

3.2.4

Precompiled Headers

There are three base header files that are provided. They can be used to precompile the standard headers and extensions into
binary files that may then be used to speed up compilations that use these headers.
• stdc++.h
Includes all standard headers. Actual content varies depending on language dialect.
• stdtr1c++.h
Includes all of , and adds all the TR1 headers.
• extc++.h
Includes all of , and adds all the Extension headers (and in C++98 mode also adds all the TR1 headers by including
all of ).

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To construct a .gch file from one of these base header files, first find the include directory for the compiler. One way to do this is:
g++ -v hello.cc
#include <...> search starts here:
/mnt/share/bld/H-x86-gcc.20071201/include/c++/4.3.0
...
End of search list.

Then, create a precompiled header file with the same flags that will be used to compile other projects.
g++ -Winvalid-pch -x c++-header -g -O2 -o ./stdc++.h.gch /mnt/share/bld/H-x86-gcc.20071201/ ←include/c++/4.3.0/x86_64-unknown-linux-gnu/bits/stdc++.h

The resulting file will be quite large: the current size is around thirty megabytes.
How to use the resulting file.
g++ -I. -include stdc++.h

-H -g -O2 hello.cc

Verification that the PCH file is being used is easy:
g++ -Winvalid-pch -I. -include stdc++.h -H -g -O2 hello.cc -o test.exe
! ./stdc++.h.gch
. /mnt/share/bld/H-x86-gcc.20071201/include/c++/4.3.0/iostream
. /mnt/share/bld/H-x86-gcc.20071201include/c++/4.3.0/string

The exclamation point to the left of the stdc++.h.gch listing means that the generated PCH file was used.
Detailed information about creating precompiled header files can be found in the GCC documentation.

3.3

Macros

All library macros begin with _GLIBCXX_.
Furthermore, all pre-processor macros, switches, and configuration options are gathered in the file c++config.h, which is
generated during the libstdc++ configuration and build process. This file is then included when needed by files part of the public
libstdc++ API, like . Most of these macros should not be used by consumers of libstdc++, and are reserved for internal
implementation use. These macros cannot be redefined.
A select handful of macros control libstdc++ extensions and extra features, or provide versioning information for the API. Only
those macros listed below are offered for consideration by the general public.
Below are the macros which users may check for library version information.
_GLIBCXX_RELEASE The major release number for libstdc++. This macro is defined to the GCC major version that the
libstdc++ headers belong to, as an integer constant. When compiling with GCC it has the same value as GCC’s pre-defined
macro __GNUC__. This macro can be used when libstdc++ is used with a non-GNU compiler where __GNUC__ is not
defined, or has a different value that doesn’t correspond to the libstdc++ version. This macro first appeared in the GCC 7.1
release and is not defined for GCC 6.x or older releases.
__GLIBCXX__ The revision date of the libstdc++ source code, in compressed ISO date format, as an unsigned long. For notes
about using this macro and details on the value of this macro for a particular release, please consult the ABI History
appendix.
Below are the macros which users may change with #define/#undef or with -D/-U compiler flags. The default state of the symbol
is listed.
“Configurable” (or “Not configurable”) means that the symbol is initially chosen (or not) based on --enable/--disable options
at library build and configure time (documented in Configure), with the various --enable/--disable choices being translated to
#define/#undef).

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ABI means that changing from the default value may mean changing the ABI of compiled code. In other words, these choices
control code which has already been compiled (i.e., in a binary such as libstdc++.a/.so). If you explicitly #define or #undef these
macros, the headers may see different code paths, but the libraries which you link against will not. Experimenting with different
values with the expectation of consistent linkage requires changing the config headers before building/installing the library.
_GLIBCXX_USE_DEPRECATED Defined by default. Not configurable. ABI-changing. Turning this off removes older ARMstyle iostreams code, and other anachronisms from the API. This macro is dependent on the version of the standard being
tracked, and as a result may give different results for -std=c++98 and -std=c++11. This may be useful in updating
old C++ code which no longer meet the requirements of the language, or for checking current code against new language
standards.
_GLIBCXX_USE_CXX11_ABI Defined to the value 1 by default. Configurable via --disable-libstdcxx-dual-abi
and/or --with-default-libstdcxx-abi. ABI-changing. When defined to a non-zero value the library headers
will use the new C++11-conforming ABI introduced in GCC 5, rather than the older ABI introduced in GCC 3.4. This
changes the definition of several class templates, including std:string, std::list and some locale facets. For more
details see Dual ABI.
_GLIBCXX_CONCEPT_CHECKS Undefined by default. Configurable via --enable-concept-checks. When defined,
performs compile-time checking on certain template instantiations to detect violations of the requirements of the standard.
This macro has no effect for freestanding implementations. This is described in more detail in Compile Time Checks.
_GLIBCXX_ASSERTIONS Undefined by default. When defined, enables extra error checking in the form of precondition
assertions, such as bounds checking in strings and null pointer checks when dereferencing smart pointers.
_GLIBCXX_DEBUG Undefined by default. When defined, compiles user code using the debug mode. When defined, _GLIBC
XX_ASSERTIONS is defined automatically, so all the assertions enabled by that macro are also enabled in debug mode.
_GLIBCXX_DEBUG_PEDANTIC Undefined by default. When defined while compiling with the debug mode, makes the debug
mode extremely picky by making the use of libstdc++ extensions and libstdc++-specific behavior into errors.
_GLIBCXX_PARALLEL Undefined by default. When defined, compiles user code using the parallel mode.
_GLIBCXX_PARALLEL_ASSERTIONS Undefined by default, but when any parallel mode header is included this macro will
be defined to a non-zero value if _GLIBCXX_ASSERTIONS has a non-zero value, otherwise to zero. When defined to a
non-zero value, it enables extra error checking and assertions in the parallel mode.
_GLIBCXX_PROFILE Undefined by default. When defined, compiles user code using the profile mode.
__STDCPP_WANT_MATH_SPEC_FUNCS__ Undefined by default. When defined to a non-zero integer constant, enables support for ISO/IEC 29124 Special Math Functions.

3.4

Dual ABI

In the GCC 5.1 release libstdc++ introduced a new library ABI that includes new implementations of std::string and std:
:list. These changes were necessary to conform to the 2011 C++ standard which forbids Copy-On-Write strings and requires
lists to keep track of their size.
In order to maintain backwards compatibility for existing code linked to libstdc++ the library’s soname has not changed and the
old implementations are still supported in parallel with the new ones. This is achieved by defining the new implementations
in an inline namespace so they have different names for linkage purposes, e.g. the new version of std::list is
actually defined as std::__cxx11::list. Because the symbols for the new implementations have different names
the definitions for both versions can be present in the same library.
The _GLIBCXX_USE_CXX11_ABI macro (see Macros) controls whether the declarations in the library headers use the old or
new ABI. So the decision of which ABI to use can be made separately for each source file being compiled. Using the default
configuration options for GCC the default value of the macro is 1 which causes the new ABI to be active, so to use the old ABI
you must explicitly define the macro to 0 before including any library headers. (Be aware that some GNU/Linux distributions
configure GCC 5 differently so that the default value of the macro is 0 and users must define it to 1 to enable the new ABI.)

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Although the changes were made for C++11 conformance, the choice of ABI to use is independent of the -std option used to
compile your code, i.e. for a given GCC build the default value of the _GLIBCXX_USE_CXX11_ABI macro is the same for
all dialects. This ensures that the -std does not change the ABI, so that it is straightforward to link C++03 and C++11 code
together.
Because std::string is used extensively throughout the library a number of other types are also defined twice, including the
stringstream classes and several facets used by std::locale. The standard facets which are always installed in a locale may
be present twice, with both ABIs, to ensure that code like std::use_facet>(locale); will
work correctly for both std::time_get and std::__cxx11::time_get (even if a user-defined facet that derives from
one or other version of time_get is installed in the locale).
Although the standard exception types defined in  use strings, they are not defined twice, so that a std::
out_of_range exception thrown in one file can always be caught by a suitable handler in another file, even if the two files are
compiled with different ABIs.

3.4.1

Troubleshooting

If you get linker errors about undefined references to symbols that involve types in the std::__cxx11 namespace or the tag
[abi:cxx11] then it probably indicates that you are trying to link together object files that were compiled with different values
for the _GLIBCXX_USE_CXX11_ABI macro. This commonly happens when linking to a third-party library that was compiled
with an older version of GCC. If the third-party library cannot be rebuilt with the new ABI then you will need to recompile your
code with the old ABI.
Not all uses of the new ABI will cause changes in symbol names, for example a class with a std::string member variable
will have the same mangled name whether compiled with the old or new ABI. In order to detect such problems the new types and
functions are annotated with the abi_tag attribute, allowing the compiler to warn about potential ABI incompatibilities in code
using them. Those warnings can be enabled with the -Wabi-tag option.

3.5
3.5.1

Namespaces
Available Namespaces

There are three main namespaces.
• std
The ISO C++ standards specify that "all library entities are defined within namespace std." This includes namespaces nested
within namespace std, such as namespace std::chrono.
• abi
Specified by the C++ ABI. This ABI specifies a number of type and function APIs supplemental to those required by the ISO
C++ Standard, but necessary for interoperability.
• __gnu_
Indicating one of several GNU extensions. Choices include __gnu_cxx, __gnu_debug, __gnu_parallel, and __gn
u_pbds.
The library uses a number of inline namespaces as implementation details that are not intended for users to refer to directly, these
include std::__detail, std::__cxx11 and std::_V2.
A complete list of implementation namespaces (including namespace contents) is available in the generated source documentation.

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namespace std

One standard requirement is that the library components are defined in namespace std::. Thus, in order to use these types
or functions, one must do one of two things:
• put a kind of using-declaration in your source (either using namespace std; or i.e. using std::string;) This
approach works well for individual source files, but should not be used in a global context, like header files.
• use a fully qualified name for each library symbol (i.e. std::string, std::cout) Always can be used, and usually
enhanced, by strategic use of typedefs. (In the cases where the qualified verbiage becomes unwieldy.)

3.5.3

Using Namespace Composition

Best practice in programming suggests sequestering new data or functionality in a sanely-named, unique namespace whenever
possible. This is considered an advantage over dumping everything in the global namespace, as then name look-up can be
explicitly enabled or disabled as above, symbols are consistently mangled without repetitive naming prefixes or macros, etc.
For instance, consider a project that defines most of its classes in namespace gtk. It is possible to adapt namespace gtk
to namespace std by using a C++-feature called namespace composition. This is what happens if a using-declaration is put
into a namespace-definition: the imported symbol(s) gets imported into the currently active namespace(s). For example:
namespace gtk
{
using std::string;
using std::tr1::array;
class Window { ... };
}

In this example, std::string gets imported into namespace gtk. The result is that use of std::string inside namespace gtk can just use string, without the explicit qualification. As an added bonus, std::string does not get imported
into the global namespace. Additionally, a more elaborate arrangement can be made for backwards compatibility and portability,
whereby the using-declarations can wrapped in macros that are set based on autoconf-tests to either "" or i.e. using std::
string; (depending on whether the system has libstdc++ in std:: or not). (ideas from Llewelly and Karl Nelson)

3.6
3.6.1

Linking
Almost Nothing

Or as close as it gets: freestanding. This is a minimal configuration, with only partial support for the standard library. Assume
only the following header files can be used:
• cstdarg
• cstddef
• cstdlib
• exception
• limits
• new
• exception
• typeinfo

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In addition, throw in
• cxxabi.h.
In the C++11 dialect add
• initializer_list
• type_traits
There exists a library that offers runtime support for just these headers, and it is called libsupc++.a. To use it, compile with
gcc instead of g++, like so:
gcc foo.cc -lsupc++
No attempt is made to verify that only the minimal subset identified above is actually used at compile time. Violations are
diagnosed as undefined symbols at link time.

3.6.2

Finding Dynamic or Shared Libraries

If the only library built is the static library (libstdc++.a), or if specifying static linking, this section is can be skipped. But if
building or using a shared library (libstdc++.so), then additional location information will need to be provided.
But how?
A quick read of the relevant part of the GCC manual, Compiling C++ Programs, specifies linking against a C++ library. More
details from the GCC FAQ, which states GCC does not, by default, specify a location so that the dynamic linker can find dynamic
libraries at runtime.
Users will have to provide this information.
Methods vary for different platforms and different styles, and are printed to the screen during installation. To summarize:
• At runtime set LD_LIBRARY_PATH in your environment correctly, so that the shared library for libstdc++ can be found and
loaded. Be certain that you understand all of the other implications and behavior of LD_LIBRARY_PATH first.
• Compile the path to find the library at runtime into the program. This can be done by passing certain options to g++, which
will in turn pass them on to the linker. The exact format of the options is dependent on which linker you use:
– GNU ld (default on GNU/Linux): -Wl,-rpath,destdir/lib
– Solaris ld: -Wl,-Rdestdir/lib
• Some linkers allow you to specify the path to the library by setting LD_RUN_PATH in your environment when linking.
• On some platforms the system administrator can configure the dynamic linker to always look for libraries in destdir/lib,
for example by using the ldconfig utility on GNU/Linux or the crle utility on Solaris. This is a system-wide change which can
make the system unusable so if you are unsure then use one of the other methods described above.
Use the ldd utility on the linked executable to show which libstdc++.so library the system will get at runtime.
A libstdc++.la file is also installed, for use with Libtool. If you use Libtool to create your executables, these details are
taken care of for you.

3.6.3

Experimental Library Extensions

GCC 5.3 includes an implementation of the Filesystem library defined by the technical specification ISO/IEC TS 18822:2015.
Because this is an experimental library extension, not part of the C++ standard, it is implemented in a separate library, libstdc+
+fs.a, and there is no shared library for it. To use the library you should include  and
link with -lstdc++fs. The library implementation is incomplete on non-POSIX platforms, specifically Windows support is
rudimentary.
Due to the experimental nature of the Filesystem library the usual guarantees about ABI stability and backwards compatibility
do not apply to it. There is no guarantee that the components in any  header will remain compatible
between different GCC releases.

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Concurrency

This section discusses issues surrounding the proper compilation of multithreaded applications which use the Standard C++
library. This information is GCC-specific since the C++ standard does not address matters of multithreaded applications.

3.7.1

Prerequisites

All normal disclaimers aside, multithreaded C++ application are only supported when libstdc++ and all user code was built
with compilers which report (via gcc/g++ -v ) the same thread model and that model is not single. As long as your final
application is actually single-threaded, then it should be safe to mix user code built with a thread model of single with a libstdc++
and other C++ libraries built with another thread model useful on the platform. Other mixes may or may not work but are not
considered supported. (Thus, if you distribute a shared C++ library in binary form only, it may be best to compile it with a GCC
configured with --enable-threads for maximal interchangeability and usefulness with a user population that may have built GCC
with either --enable-threads or --disable-threads.)
When you link a multithreaded application, you will probably need to add a library or flag to g++. This is a very non-standardized
area of GCC across ports. Some ports support a special flag (the spelling isn’t even standardized yet) to add all required macros to
a compilation (if any such flags are required then you must provide the flag for all compilations not just linking) and link-library
additions and/or replacements at link time. The documentation is weak. On several targets (including GNU/Linux, Solaris and
various BSDs) -pthread is honored. Some other ports use other switches. This is not well documented anywhere other than in
"gcc -dumpspecs" (look at the ’lib’ and ’cpp’ entries).
Some uses of std::atomic also require linking to libatomic.

3.7.2

Thread Safety

In the terms of the 2011 C++ standard a thread-safe program is one which does not perform any conflicting non-atomic operations
on memory locations and so does not contain any data races. The standard places requirements on the library to ensure that no
data races are caused by the library itself or by programs which use the library correctly (as described below). The C++11
memory model and library requirements are a more formal version of the SGI STL definition of thread safety, which the library
used prior to the 2011 standard.
The library strives to be thread-safe when all of the following conditions are met:
• The system’s libc is itself thread-safe,
• The compiler in use reports a thread model other than ’single’. This can be tested via output from gcc -v. Multi-thread
capable versions of gcc output something like this:
%gcc -v
Using built-in specs.
...
Thread model: posix
gcc version 4.1.2 20070925 (Red Hat 4.1.2-33)

Look for "Thread model" lines that aren’t equal to "single."
• Requisite command-line flags are used for atomic operations and threading. Examples of this include -pthread and march=native, although specifics vary depending on the host environment. See Command Options and Machine Dependent
Options.
• An implementation of the atomicity.h functions exists for the architecture in question. See the internals documentation
for more details.
The user code must guard against concurrent function calls which access any particular library object’s state when one or more
of those accesses modifies the state. An object will be modified by invoking a non-const member function on it or passing it as a
non-const argument to a library function. An object will not be modified by invoking a const member function on it or passing it
to a function as a pointer- or reference-to-const. Typically, the application programmer may infer what object locks must be held
based on the objects referenced in a function call and whether the objects are accessed as const or non-const. Without getting
into great detail, here is an example which requires user-level locks:

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library_class_a shared_object_a;
void thread_main () {
library_class_b *object_b = new library_class_b;
shared_object_a.add_b (object_b);
// must hold lock for shared_object_a
shared_object_a.mutate ();
// must hold lock for shared_object_a
}
// Multiple copies of thread_main() are started in independent threads.

Under the assumption that object_a and object_b are never exposed to another thread, here is an example that does not require
any user-level locks:
void thread_main () {
library_class_a object_a;
library_class_b *object_b = new library_class_b;
object_a.add_b (object_b);
object_a.mutate ();
}

All library types are safe to use in a multithreaded program if objects are not shared between threads or as long each thread carefully locks out access by any other thread while it modifies any object visible to another thread. Unless otherwise documented,
the only exceptions to these rules are atomic operations on the types in  and lock/unlock operations on the standard
mutex types in . These atomic operations allow concurrent accesses to the same object without introducing data races.
The following member functions of standard containers can be considered to be const for the purposes of avoiding data races:
begin, end, rbegin, rend, front, back, data, find, lower_bound, upper_bound, equal_range, at and,
except in associative or unordered associative containers, operator[]. In other words, although they are non-const so that
they can return mutable iterators, those member functions will not modify the container. Accessing an iterator might cause a
non-modifying access to the container the iterator refers to (for example incrementing a list iterator must access the pointers
between nodes, which are part of the container and so conflict with other accesses to the container).
Programs which follow the rules above will not encounter data races in library code, even when using library types which share
state between distinct objects. In the example below the shared_ptr objects share a reference count, but because the code
does not perform any non-const operations on the globally-visible object, the library ensures that the reference count updates are
atomic and do not introduce data races:
std::shared_ptr global_sp;
void thread_main() {
auto local_sp = global_sp;

// OK, copy constructor’s parameter is reference-to-const

int i = *global_sp;
int j = *local_sp;

// OK, operator* is const
// OK, does not operate on global_sp

// *global_sp = 2;
// *local_sp = 2;

// NOT OK, modifies int visible to other threads
// NOT OK, modifies int visible to other threads

// global_sp.reset();
local_sp.reset();

// NOT OK, reset is non-const
// OK, does not operate on global_sp

}
int main() {
global_sp.reset(new int(1));
std::thread t1(thread_main);
std::thread t2(thread_main);
t1.join();
t2.join();
}

For further details of the C++11 memory model see Hans-J. Boehm’s Threads and memory model for C++ pages, particularly
the introduction and FAQ.

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Atomics

3.7.4

IO

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This gets a bit tricky. Please read carefully, and bear with me.
3.7.4.1

Structure

A wrapper type called __basic_file provides our abstraction layer for the std::filebuf classes. Nearly all decisions
dealing with actual input and output must be made in __basic_file.
A generic locking mechanism is somewhat in place at the filebuf layer, but is not used in the current code. Providing locking at
any higher level is akin to providing locking within containers, and is not done for the same reasons (see the links above).
3.7.4.2

Defaults

The __basic_file type is simply a collection of small wrappers around the C stdio layer (again, see the link under Structure). We
do no locking ourselves, but simply pass through to calls to fopen, fwrite, and so forth.
So, for 3.0, the question of "is multithreading safe for I/O" must be answered with, "is your platform’s C library threadsafe
for I/O?" Some are by default, some are not; many offer multiple implementations of the C library with varying tradeoffs of
threadsafety and efficiency. You, the programmer, are always required to take care with multiple threads.
(As an example, the POSIX standard requires that C stdio FILE* operations are atomic. POSIX-conforming C libraries (e.g,
on Solaris and GNU/Linux) have an internal mutex to serialize operations on FILE*s. However, you still need to not do stupid
things like calling fclose(fs) in one thread followed by an access of fs in another.)
So, if your platform’s C library is threadsafe, then your fstream I/O operations will be threadsafe at the lowest level. For
higher-level operations, such as manipulating the data contained in the stream formatting classes (e.g., setting up callbacks inside
an std::ofstream), you need to guard such accesses like any other critical shared resource.
3.7.4.3

Future

A second choice may be available for I/O implementations: libio. This is disabled by default, and in fact will not currently work
due to other issues. It will be revisited, however.
The libio code is a subset of the guts of the GNU libc (glibc) I/O implementation. When libio is in use, the __basic_file
type is basically derived from FILE. (The real situation is more complex than that... it’s derived from an internal type used to
implement FILE. See libio/libioP.h to see scary things done with vtbls.) The result is that there is no "layer" of C stdio to go
through; the filebuf makes calls directly into the same functions used to implement fread, fwrite, and so forth, using internal
data structures. (And when I say "makes calls directly," I mean the function is literally replaced by a jump into an internal
function. Fast but frightening. *grin*)
Also, the libio internal locks are used. This requires pulling in large chunks of glibc, such as a pthreads implementation, and is
one of the issues preventing widespread use of libio as the libstdc++ cstdio implementation.
But we plan to make this work, at least as an option if not a future default. Platforms running a copy of glibc with a recent-enough
version will see calls from libstdc++ directly into the glibc already installed. For other platforms, a copy of the libio subsection
will be built and included in libstdc++.
3.7.4.4

Alternatives

Don’t forget that other cstdio implementations are possible. You could easily write one to perform your own forms of locking, to
solve your "interesting" problems.

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Containers

This section discusses issues surrounding the design of multithreaded applications which use Standard C++ containers. All
information in this section is current as of the gcc 3.0 release and all later point releases. Although earlier gcc releases had a
different approach to threading configuration and proper compilation, the basic code design rules presented here were similar.
For information on all other aspects of multithreading as it relates to libstdc++, including details on the proper compilation of
threaded code (and compatibility between threaded and non-threaded code), see Chapter 17.
Two excellent pages to read when working with the Standard C++ containers and threads are SGI’s http://www.sgi.com/tech/stl/thread_safety.html and SGI’s http://www.sgi.com/tech/stl/Allocators.html.
However, please ignore all discussions about the user-level configuration of the lock implementation inside the STL containermemory allocator on those pages. For the sake of this discussion, libstdc++ configures the SGI STL implementation, not you.
This is quite different from how gcc pre-3.0 worked. In particular, past advice was for people using g++ to explicitly define
_PTHREADS or other macros or port-specific compilation options on the command line to get a thread-safe STL. This is no
longer required for any port and should no longer be done unless you really know what you are doing and assume all responsibility.
Since the container implementation of libstdc++ uses the SGI code, we use the same definition of thread safety as SGI when
discussing design. A key point that beginners may miss is the fourth major paragraph of the first page mentioned above (For
most clients...), which points out that locking must nearly always be done outside the container, by client code (that’d be you,
not us). There is a notable exceptions to this rule. Allocators called while a container or element is constructed uses an internal
lock obtained and released solely within libstdc++ code (in fact, this is the reason STL requires any knowledge of the thread
configuration).
For implementing a container which does its own locking, it is trivial to provide a wrapper class which obtains the lock (as SGI
suggests), performs the container operation, and then releases the lock. This could be templatized to a certain extent, on the
underlying container and/or a locking mechanism. Trying to provide a catch-all general template solution would probably be
more trouble than it’s worth.
The library implementation may be configured to use the high-speed caching memory allocator, which complicates thread safety
issues. For all details about how to globally override this at application run-time see here. Also useful are details on allocator
options and capabilities.

3.8

Exceptions

The C++ language provides language support for stack unwinding with try and catch blocks and the throw keyword.
These are very powerful constructs, and require some thought when applied to the standard library in order to yield components
that work efficiently while cleaning up resources when unexpectedly killed via exceptional circumstances.
Two general topics of discussion follow: exception neutrality and exception safety.

3.8.1

Exception Safety

What is exception-safe code?
Will define this as reasonable and well-defined behavior by classes and functions from the standard library when used by userdefined classes and functions that are themselves exception safe.
Please note that using exceptions in combination with templates imposes an additional requirement for exception safety. Instantiating types are required to have destructors that do no throw.
Using the layered approach from Abrahams, can classify library components as providing set levels of safety. These will be
called exception guarantees, and can be divided into three categories.
• One. Don’t throw.
As specified in 23.2.1 general container requirements. Applicable to container and string classes.
Member functions erase, pop_back, pop_front, swap, clear. And iterator copy constructor and assignment operator.

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• Two. Don’t leak resources when exceptions are thrown. This is also referred to as the “basic” exception safety guarantee.
This applicable throughout the standard library.
• Three. Commit-or-rollback semantics. This is referred to as “strong” exception safety guarantee.
As specified in 23.2.1 general container requirements. Applicable to container and string classes.
Member functions insert of a single element, push_back, push_front, and rehash.

3.8.2

Exception Neutrality

Simply put, once thrown an exception object should continue in flight unless handled explicitly. In practice, this means propagating exceptions should not be swallowed in gratuitous catch(...) blocks. Instead, matching try and catch blocks should
have specific catch handlers and allow un-handed exception objects to propagate. If a terminating catch(...) blocks exist
then it should end with a throw to re-throw the current exception.
Why do this?
By allowing exception objects to propagate, a more flexible approach to error handling is made possible (although not required.)
Instead of dealing with an error immediately, one can allow the exception to propagate up until sufficient context is available and
the choice of exiting or retrying can be made in an informed manner.
Unfortunately, this tends to be more of a guideline than a strict rule as applied to the standard library. As such, the following is a
list of known problem areas where exceptions are not propagated.
• Input/Output
The destructor ios_base::Init::~Init() swallows all exceptions from flush called on all open streams at termination.
All formatted input in basic_istream or formatted output in basic_ostream can be configured to swallow exceptions
when exceptions is set to ignore ios_base::badbit.
Functions that have been registered with ios_base::register_callback swallow all exceptions when called as part
of a callback event.
When closing the underlying file, basic_filebuf::close will swallow (non-cancellation) exceptions thrown and return
NULL.
• Thread
The constructors of thread that take a callable function argument swallow all exceptions resulting from executing the function
argument.

3.8.3

Doing without

C++ is a language that strives to be as efficient as is possible in delivering features. As such, considerable care is used by both
language implementer and designers to make sure unused features not impose hidden or unexpected costs. The GNU system
tries to be as flexible and as configurable as possible. So, it should come as no surprise that GNU C++ provides an optional
language extension, spelled -fno-exceptions, as a way to excise the implicitly generated magic necessary to support try
and catch blocks and thrown objects. (Language support for -fno-exceptions is documented in the GNU GCC manual.)
Before detailing the library support for -fno-exceptions, first a passing note on the things lost when this flag is used: it
will break exceptions trying to pass through code compiled with -fno-exceptions whether or not that code has any try or
catch constructs. If you might have some code that throws, you shouldn’t use -fno-exceptions. If you have some code
that uses try or catch, you shouldn’t use -fno-exceptions.
And what it to be gained, tinkering in the back alleys with a language like this? Exception handling overhead can be measured
in the size of the executable binary, and varies with the capabilities of the underlying operating system and specific configuration
of the C++ compiler. On recent hardware with GNU system software of the same age, the combined code and data size overhead
for enabling exception handling is around 7%. Of course, if code size is of singular concern than using the appropriate optimizer
setting with exception handling enabled (ie, -Os -fexceptions) may save up to twice that, and preserve error checking.

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So. Hell bent, we race down the slippery track, knowing the brakes are a little soft and that the right front wheel has a tendency
to wobble at speed. Go on: detail the standard library support for -fno-exceptions.
In sum, valid C++ code with exception handling is transformed into a dialect without exception handling. In detailed steps: all use
of the C++ keywords try, catch, and throw in the standard library have been permanently replaced with the pre-processor
controlled equivalents spelled __try, __catch, and __throw_exception_again. They are defined as follows.
#if __cpp_exceptions
# define __try
try
# define __catch(X) catch(X)
# define __throw_exception_again throw
#else
# define __try
if (true)
# define __catch(X) if (false)
# define __throw_exception_again
#endif

In addition, for every object derived from class exception, there exists a corresponding function with C language linkage. An
example:
#if __cpp_exceptions
void __throw_bad_exception(void)
{ throw bad_exception(); }
#else
void __throw_bad_exception(void)
{ abort(); }
#endif

The last language feature needing to be transformed by -fno-exceptions is treatment of exception specifications on member
functions. Fortunately, the compiler deals with this by ignoring exception specifications and so no alternate source markup is
needed.
By using this combination of language re-specification by the compiler, and the pre-processor tricks and the functional indirection
layer for thrown exception objects by the library, libstdc++ files can be compiled with -fno-exceptions.
User code that uses C++ keywords like throw, try, and catch will produce errors even if the user code has included libstdc++
headers and is using constructs like basic_iostream. Even though the standard library has been transformed, user code may
need modification. User code that attempts or expects to do error checking on standard library components compiled with
exception handling disabled should be evaluated and potentially made conditional.
Some issues remain with this approach (see bugzilla entry 25191). Code paths are not equivalent, in particular catch blocks
are not evaluated. Also problematic are throw expressions expecting a user-defined throw handler. Known problem areas in the
standard library include using an instance of basic_istream with exceptions set to specific ios_base::iostate conditions,
or cascading catch blocks that dispatch error handling or recovery efforts based on the type of exception object thrown.
Oh, and by the way: none of this hackery is at all special. (Although perhaps well-deserving of a raised eyebrow.) Support
continues to evolve and may change in the future. Similar and even additional techniques are used in other C++ libraries and
compilers.
C++ hackers with a bent for language and control-flow purity have been successfully consoled by grizzled C veterans lamenting
the substitution of the C language keyword const with the uglified doppelganger __const.

3.8.4

Compatibility

3.8.4.1

With C

C language code that is expecting to interoperate with C++ should be compiled with -fexceptions. This will make debugging
a C language function called as part of C++-induced stack unwinding possible.
In particular, unwinding into a frame with no exception handling data will cause a runtime abort. If the unwinder runs out of
unwind info before it finds a handler, std::terminate() is called.
Please note that most development environments should take care of getting these details right. For GNU systems, all appropriate
parts of the GNU C library are already compiled with -fexceptions.

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With POSIX thread cancellation

GNU systems re-use some of the exception handling mechanisms to track control flow for POSIX thread cancellation.
Cancellation points are functions defined by POSIX as worthy of special treatment. The standard library may use some of these
functions to implement parts of the ISO C++ standard or depend on them for extensions.
Of note:
nanosleep, read, write, open, close, and wait.
The parts of libstdc++ that use C library functions marked as cancellation points should take pains to be exception neutral. Failing
this, catch blocks have been augmented to show that the POSIX cancellation object is in flight.
This augmentation adds a catch block for __cxxabiv1::__forced_unwind, which is the object representing the POSIX
cancellation object. Like so:
catch(const __cxxabiv1::__forced_unwind&)
{
this->_M_setstate(ios_base::badbit);
throw;
}
catch(...)
{ this->_M_setstate(ios_base::badbit); }

3.8.5

Bibliography
[1] System Interface Definitions, Issue 7 (IEEE Std. 1003.1-2008) , 2.9.5 Thread Cancellation , Copyright © 2008
The Open Group/The Institute of Electrical and Electronics Engineers, Inc. .
[2] David Abrahams , Error and Exception Handling , Boost .
[3] David Abrahams, Exception-Safety in Generic Components , Boost .
[4] Matt Austern, Standard Library Exception Policy , WG21 N1077 .
[5] Richard Henderson, ia64 c++ abi exception handling , GNU .
[6] Bjarne Stroustrup, Appendix E: Standard-Library Exception Safety
[7] Herb Sutter, Exception-Safety Issues and Techniques .
[8] GCC Bug 25191: exception_defines.h #defines try/catch

3.9

Debugging Support

There are numerous things that can be done to improve the ease with which C++ binaries are debugged when using the GNU
tool chain. Here are some of them.

3.9.1

Using g++

Compiler flags determine how debug information is transmitted between compilation and debug or analysis tools.
The default optimizations and debug flags for a libstdc++ build are -g -O2. However, both debug and optimization flags
can be varied to change debugging characteristics. For instance, turning off all optimization via the -g -O0 -fno-inline
flags will disable inlining and optimizations, and add debugging information, so that stepping through all functions, (including
inlined constructors and destructors) is possible. In addition, -fno-eliminate-unused-debug-types can be used when
additional debug information, such as nested class info, is desired.

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Or, the debug format that the compiler and debugger use to communicate information about source constructs can be changed
via -gdwarf-2 or -gstabs flags: some debugging formats permit more expressive type and scope information to be shown
in GDB. Expressiveness can be enhanced by flags like -g3. The default debug information for a particular platform can be
identified via the value set by the PREFERRED_DEBUGGING_TYPE macro in the GCC sources.
Many other options are available: please see "Options for Debugging Your Program" in Using the GNU Compiler Collection
(GCC) for a complete list.

3.9.2

Debug Versions of Library Binary Files

If you would like debug symbols in libstdc++, there are two ways to build libstdc++ with debug flags. The first is to create a
separate debug build by running make from the top-level of a tree freshly-configured with
--enable-libstdcxx-debug

and perhaps
--enable-libstdcxx-debug-flags=’...’

Both the normal build and the debug build will persist, without having to specify CXXFLAGS, and the debug library will be
installed in a separate directory tree, in (prefix)/lib/debug. For more information, look at the configuration section.
A second approach is to use the configuration flags
make CXXFLAGS=’-g3 -fno-inline -O0’ all

This quick and dirty approach is often sufficient for quick debugging tasks, when you cannot or don’t want to recompile your
application to use the debug mode.

3.9.3

Memory Leak Hunting

There are various third party memory tracing and debug utilities that can be used to provide detailed memory allocation information about C++ code. An exhaustive list of tools is not going to be attempted, but includes mtrace, valgrind, mudflap,
and the non-free commercial product purify. In addition, libcwd has a replacement for the global new and delete operators
that can track memory allocation and deallocation and provide useful memory statistics.
Regardless of the memory debugging tool being used, there is one thing of great importance to keep in mind when debugging
C++ code that uses new and delete: there are different kinds of allocation schemes that can be used by std::allocator.
For implementation details, see the mt allocator documentation and look specifically for GLIBCXX_FORCE_NEW.
In a nutshell, the optional mt_allocator is a high-performance pool allocator, and can give the mistaken impression that in
a suspect executable, memory is being leaked, when in reality the memory "leak" is a pool being used by the library’s allocator
and is reclaimed after program termination.
For valgrind, there are some specific items to keep in mind. First of all, use a version of valgrind that will work with current
GNU C++ tools: the first that can do this is valgrind 1.0.4, but later versions should work at least as well. Second of all, use
a completely unoptimized build to avoid confusing valgrind. Third, use GLIBCXX_FORCE_NEW to keep extraneous pool
allocation noise from cluttering debug information.
Fourth, it may be necessary to force deallocation in other libraries as well, namely the "C" library. On linux, this can be
accomplished with the appropriate use of the __cxa_atexit or atexit functions.
#include 
extern "C" void __libc_freeres(void);
void do_something() { }
int main()
{

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atexit(__libc_freeres);
do_something();
return 0;
}

or, using __cxa_atexit:
extern "C" void __libc_freeres(void);
extern "C" int __cxa_atexit(void (*func) (void *), void *arg, void *d);
void do_something() { }
int main()
{
extern void* __dso_handle __attribute__ ((__weak__));
__cxa_atexit((void (*) (void *)) __libc_freeres, NULL,
&__dso_handle ? __dso_handle : NULL);
do_test();
return 0;
}

Suggested valgrind flags, given the suggestions above about setting up the runtime environment, library, and test file, might be:
valgrind -v --num-callers=20 --leak-check=yes --leak-resolution=high --show-reachable= ←yes a.out

3.9.4

Data Race Hunting

All synchronization primitives used in the library internals need to be understood by race detectors so that they do not produce
false reports.
Two annotation macros are used to explain low-level synchronization to race detectors: _GLIBCXX_SYNCHRONIZATION_H
APPENS_BEFORE() and _GLIBCXX_SYNCHRONIZATION_HAPPENS_AFTER(). By default, these macros are defined
empty -- anyone who wants to use a race detector needs to redefine them to call an appropriate API. Since these macros are
empty by default when the library is built, redefining them will only affect inline functions and template instantiations which are
compiled in user code. This allows annotation of templates such as shared_ptr, but not code which is only instantiated in
the library. Code which is only instantiated in the library needs to be recompiled with the annotation macros defined. That can
be done by rebuilding the entire libstdc++.so file but a simpler alternative exists for ELF platforms such as GNU/Linux,
because ELF symbol interposition allows symbols defined in the shared library to be overridden by symbols with the same
name that appear earlier in the runtime search path. This means you only need to recompile the functions that are affected
by the annotation macros, which can be done by recompiling individual files. Annotating std::string and std::wst
ring reference counting can be done by disabling extern templates (by defining _GLIBCXX_EXTERN_TEMPLATE=-1) or
by rebuilding the src/string-inst.cc file. Annotating the remaining atomic operations (at the time of writing these
are in ios_base::Init::~Init, locale::_Impl, locale::facet and thread::_M_start_thread) requires
rebuilding the relevant source files.
The approach described above is known to work with the following race detection tools: DRD, Helgrind, and ThreadSanitizer
(this refers to ThreadSanitizer v1, not the new "tsan" feature built-in to GCC itself).
With DRD, Helgrind and ThreadSanitizer you will need to define the macros like this:
#define _GLIBCXX_SYNCHRONIZATION_HAPPENS_BEFORE(A) ANNOTATE_HAPPENS_BEFORE(A)
#define _GLIBCXX_SYNCHRONIZATION_HAPPENS_AFTER(A) ANNOTATE_HAPPENS_AFTER(A)

Refer to the documentation of each particular tool for details.

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Using gdb

Many options are available for GDB itself: please see "GDB features for C++" in the GDB documentation. Also recommended:
the other parts of this manual.
These settings can either be switched on in at the GDB command line, or put into a .gdbinit file to establish default debugging
characteristics, like so:
set
set
set
set
set
set

print pretty on
print object on
print static-members on
print vtbl on
print demangle on
demangle-style gnu-v3

Starting with version 7.0, GDB includes support for writing pretty-printers in Python. Pretty printers for containers and other
classes are distributed with GCC from version 4.5.0 and should be installed alongside the libstdc++ shared library files and found
automatically by GDB.
Depending where libstdc++ is installed, GDB might refuse to auto-load the python printers and print a warning instead. If this
happens the python printers can be enabled by following the instructions GDB gives for setting your auto-load safe-path
in your .gdbinit configuration file.
Once loaded, standard library classes that the printers support should print in a more human-readable format. To print the classes
in the old style, use the /r (raw) switch in the print command (i.e., print /r foo). This will print the classes as if the Python
pretty-printers were not loaded.
For additional information on STL support and GDB please visit: "GDB Support for STL" in the GDB wiki. Additionally,
in-depth documentation and discussion of the pretty printing feature can be found in "Pretty Printing" node in the GDB manual.
You can find on-line versions of the GDB user manual in GDB’s homepage, at "GDB: The GNU Project Debugger" .

3.9.6

Tracking uncaught exceptions

The verbose termination handler gives information about uncaught exceptions which kill the program.

3.9.7

Debug Mode

The Debug Mode has compile and run-time checks for many containers.

3.9.8

Compile Time Checking

The Compile-Time Checks extension has compile-time checks for many algorithms.

3.9.9

Profile-based Performance Analysis

The Profile-based Performance Analysis extension has performance checks for many algorithms.

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Part II

Standard Contents

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Chapter 4

Support
This part deals with the functions called and objects created automatically during the course of a program’s existence.
While we can’t reproduce the contents of the Standard here (you need to get your own copy from your nation’s member body;
see our homepage for help), we can mention a couple of changes in what kind of support a C++ program gets from the Standard
Library.

4.1
4.1.1

Types
Fundamental Types

C++ has the following builtin types:
• char
• signed char
• unsigned char
• signed short
• signed int
• signed long
• unsigned short
• unsigned int
• unsigned long
• bool
• wchar_t
• float
• double
• long double
These fundamental types are always available, without having to include a header file. These types are exactly the same in either
C++ or in C.
Specializing parts of the library on these types is prohibited: instead, use a POD.

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Numeric Properties

The header limits defines traits classes to give access to various implementation defined-aspects of the fundamental types.
The traits classes -- fourteen in total -- are all specializations of the template class numeric_limits, documented here and
defined as follows:
template
struct class
{
static const bool is_specialized;
static T max() throw();
static T min() throw();
static
static
static
static
static
static
static
static

const int digits;
const int digits10;
const bool is_signed;
const bool is_integer;
const bool is_exact;
const int radix;
T epsilon() throw();
T round_error() throw();

static
static
static
static

const
const
const
const

static
static
static
static
static
static
static
static

const bool has_infinity;
const bool has_quiet_NaN;
const bool has_signaling_NaN;
const float_denorm_style has_denorm;
const bool has_denorm_loss;
T infinity() throw();
T quiet_NaN() throw();
T denorm_min() throw();

int
int
int
int

min_exponent;
min_exponent10;
max_exponent;
max_exponent10;

static const bool is_iec559;
static const bool is_bounded;
static const bool is_modulo;
static const bool traps;
static const bool tinyness_before;
static const float_round_style round_style;
};

4.1.3

NULL

The only change that might affect people is the type of NULL: while it is required to be a macro, the definition of that macro is
not allowed to be (void*)0, which is often used in C.
For g++, NULL is #define’d to be __null, a magic keyword extension of g++.
The biggest problem of #defining NULL to be something like “0L” is that the compiler will view that as a long integer before it
views it as a pointer, so overloading won’t do what you expect. (This is why g++ has a magic extension, so that NULL is always
a pointer.)
In his book Effective C++, Scott Meyers points out that the best way to solve this problem is to not overload on pointer-vs-integer
types to begin with. He also offers a way to make your own magic NULL that will match pointers before it matches integers.
See the Effective C++ CD example.

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Dynamic Memory

There are six flavors each of new and delete, so make certain that you’re using the right ones. Here are quickie descriptions
of new:
• single object form, throwing a bad_alloc on errors; this is what most people are used to using
• Single object "nothrow" form, returning NULL on errors
• Array new, throwing bad_alloc on errors
• Array nothrow new, returning NULL on errors
• Placement new, which does nothing (like it’s supposed to)
• Placement array new, which also does nothing
They are distinguished by the parameters that you pass to them, like any other overloaded function. The six flavors of delete
are distinguished the same way, but none of them are allowed to throw an exception under any circumstances anyhow. (They
match up for completeness’ sake.)
Remember that it is perfectly okay to call delete on a NULL pointer! Nothing happens, by definition. That is not the same
thing as deleting a pointer twice.
By default, if one of the “throwing news” can’t allocate the memory requested, it tosses an instance of a bad_alloc exception
(or, technically, some class derived from it). You can change this by writing your own function (called a new-handler) and then
registering it with set_new_handler():
typedef void (*PFV)(void);
static char*
static PFV

safety;
old_handler;

void my_new_handler ()
{
delete[] safety;
popup_window ("Dude, you are running low on heap memory.
" should, like, close some windows, or something."
" The next time you run out, we’re gonna burn!");
set_new_handler (old_handler);
return;
}

You"

int main ()
{
safety = new char[500000];
old_handler = set_new_handler (&my_new_handler);
...
}

bad_alloc is derived from the base exception class defined in Sect1 19.

4.3
4.3.1

Termination
Termination Handlers

Not many changes here to cstdlib. You should note that the abort() function does not call the destructors of automatic nor
static objects, so if you’re depending on those to do cleanup, it isn’t going to happen. (The functions registered with atexit()
don’t get called either, so you can forget about that possibility, too.)
The good old exit() function can be a bit funky, too, until you look closer. Basically, three points to remember are:

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1. Static objects are destroyed in reverse order of their creation.
2. Functions registered with atexit() are called in reverse order of registration, once per registration call. (This isn’t
actually new.)
3. The previous two actions are “interleaved,” that is, given this pseudocode:
extern "C or C++" void
extern "C or C++" void

f1 (void);
f2 (void);

static Thing obj1;
atexit(f1);
static Thing obj2;
atexit(f2);

then at a call of exit(), f2 will be called, then obj2 will be destroyed, then f1 will be called, and finally obj1 will
be destroyed. If f1 or f2 allow an exception to propagate out of them, Bad Things happen.
Note also that atexit() is only required to store 32 functions, and the compiler/library might already be using some of those
slots. If you think you may run out, we recommend using the xatexit/xexit combination from libiberty, which has no
such limit.

4.3.2

Verbose Terminate Handler

If you are having difficulty with uncaught exceptions and want a little bit of help debugging the causes of the core dumps, you
can make use of a GNU extension, the verbose terminate handler.
#include 
int main()
{
std::set_terminate(__gnu_cxx::__verbose_terminate_handler);
...
throw anything;
}

The __verbose_terminate_handler function obtains the name of the current exception, attempts to demangle it, and
prints it to stderr. If the exception is derived from exception then the output from what() will be included.
Any replacement termination function is required to kill the program without returning; this one calls abort.
For example:
#include 
#include 
struct argument_error : public std::runtime_error
{
argument_error(const std::string& s): std::runtime_error(s) { }
};
int main(int argc)
{
std::set_terminate(__gnu_cxx::__verbose_terminate_handler);
if (argc > 5)
throw argument_error("argc is greater than 5!");
else
throw argc;
}

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With the verbose terminate handler active, this gives:
% ./a.out
terminate called after throwing a ‘int’
Aborted
% ./a.out f f f f f f f f f f f
terminate called after throwing an instance of ‘argument_error’
what(): argc is greater than 5!
Aborted

The ’Aborted’ line comes from the call to abort(), of course.
This is the default termination handler; nothing need be done to use it. To go back to the previous “silent death” method, simply
include exception and cstdlib, and call
std::set_terminate(std::abort);

After this, all calls to terminate will use abort as the terminate handler.
Note: the verbose terminate handler will attempt to write to stderr. If your application closes stderr or redirects it to an inappropriate location, __verbose_terminate_handler will behave in an unspecified manner.

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Chapter 5

Diagnostics
5.1
5.1.1

Exceptions
API Reference

All exception objects are defined in one of the standard header files: exception, stdexcept, new, and typeinfo.
The base exception object is exception, located in exception. This object has no string member.
Derived from this are several classes that may have a string member: a full hierarchy can be found in the source documentation.
Full API details.

5.1.2

Adding Data to exception

The standard exception classes carry with them a single string as data (usually describing what went wrong or where the ’throw’
took place). It’s good to remember that you can add your own data to these exceptions when extending the hierarchy:
struct My_Exception : public std::runtime_error
{
public:
My_Exception (const string& whatarg)
: std::runtime_error(whatarg), e(errno), id(GetDataBaseID()) { }
int errno_at_time_of_throw() const { return e; }
DBID id_of_thing_that_threw() const { return id; }
protected:
int
e;
DBID
id;
// some user-defined type
};

5.2

Use of errno by the library

The C and POSIX standards guarantee that errno is never set to zero by any library function. The C++ standard has less to say
about when errno is or isn’t set, but libstdc++ follows the same rule and never sets it to zero.
On the other hand, there are few guarantees about when the C++ library sets errno on error, beyond what is specified for
functions that come from the C library. For example, when std::stoi throws an exception of type std::out_of_range,
errno may or may not have been set to ERANGE.
Parts of the C++ library may be implemented in terms of C library functions, which may result in errno being set with no
explicit call to a C function. For example, on a target where operator new uses malloc a failed memory allocation with
operator new might set errno to ENOMEM. Which C++ library functions can set errno in this way is unspecified because
it may vary between platforms and between releases.

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Concept Checking

In 1999, SGI added “concept checkers” to their implementation of the STL: code which checked the template parameters of
instantiated pieces of the STL, in order to insure that the parameters being used met the requirements of the standard. For
example, the Standard requires that types passed as template parameters to vector be "Assignable" (which means what you
think it means). The checking was done during compilation, and none of the code was executed at runtime.
Unfortunately, the size of the compiler files grew significantly as a result. The checking code itself was cumbersome. And bugs
were found in it on more than one occasion.
The primary author of the checking code, Jeremy Siek, had already started work on a replacement implementation. The new
code was formally reviewed and accepted into the Boost libraries, and we are pleased to incorporate it into the GNU C++ library.
The new version imposes a much smaller space overhead on the generated object file. The checks are also cleaner and easier to
read and understand.
They are off by default for all versions of GCC. They can be enabled at configure time with --enable-concept-checks. You can
enable them on a per-translation-unit basis with -D_GLIBCXX_CONCEPT_CHECKS.
Please note that the checks are based on the requirements in the original C++ standard, many of which were relaxed in the C++11
standard and so valid C++11 code may be incorrectly rejected by the concept checks. Additionally, some correct C++03 code
might be rejected by the concept checks, for example template argument types may need to be complete when used in a template
definition, rather than at the point of instantiation. There are no plans to address these shortcomings.

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Chapter 6

Utilities
6.1

Functors

If you don’t know what functors are, you’re not alone. Many people get slightly the wrong idea. In the interest of not reinventing the wheel, we will refer you to the introduction to the functor concept written by SGI as part of their STL, in their
http://www.sgi.com/tech/stl/functors.html.

6.2

Pairs

The pair is a simple and handy way to carry around a pair of objects. One is of type T1, and another of type T2; they
may be the same type, but you don’t get anything extra if they are. The two members can be accessed directly, as .first and
.second.
Construction is simple. The default ctor initializes each member with its respective default ctor. The other simple ctor,
pair (const T1& x, const T2& y);

does what you think it does, first getting x and second getting y.
There is a constructor template for copying pairs of other types:
template  pair (const pair& p);

The compiler will convert as necessary from U to T1 and from V to T2 in order to perform the respective initializations.
The comparison operators are done for you. Equality of two pairs is defined as both first members comparing equal and both second members comparing equal; this simply delegates responsibility to the respective operator==
functions (for types like MyClass) or builtin comparisons (for types like int, char, etc).
The less-than operator is a bit odd the first time you see it. It is defined as evaluating to:
x.first < y.first ||
( !(y.first < x.first) &&

x.second

<

y.second )

The other operators are not defined using the rel_ops functions above, but their semantics are the same.
Finally, there is a template function called make_pair that takes two references-to-const objects and returns an instance of a
pair instantiated on their respective types:
pair p = make_pair(4,myobject);

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Memory

Memory contains three general areas. First, function and operator calls via new and delete operator or member function calls.
Second, allocation via allocator. And finally, smart pointer and intelligent pointer abstractions.

6.3.1

Allocators

Memory management for Standard Library entities is encapsulated in a class template called allocator. The allocator
abstraction is used throughout the library in string, container classes, algorithms, and parts of iostreams. This class, and base
classes of it, are the superset of available free store (“heap”) management classes.
6.3.1.1

Requirements

The C++ standard only gives a few directives in this area:
• When you add elements to a container, and the container must allocate more memory to hold them, the container makes the
request via its Allocator template parameter, which is usually aliased to allocator_type. This includes adding chars to the string
class, which acts as a regular STL container in this respect.
• The default Allocator argument of every container-of-T is allocator.
• The interface of the allocator class is extremely simple. It has about 20 public declarations (nested typedefs, member
functions, etc), but the two which concern us most are:
T*
void

allocate
(size_type n, const void* hint = 0);
deallocate (T* p, size_type n);

The n arguments in both those functions is a count of the number of T’s to allocate space for, not their total size. (This is a
simplification; the real signatures use nested typedefs.)
• The storage is obtained by calling ::operator new, but it is unspecified when or how often this function is called. The use
of the hint is unspecified, but intended as an aid to locality if an implementation so desires. [20.4.1.1]/6
Complete details can be found in the C++ standard, look in [20.4 Memory].
6.3.1.2

Design Issues

The easiest way of fulfilling the requirements is to call operator new each time a container needs memory, and to call
operator delete each time the container releases memory. This method may be slower than caching the allocations and reusing previously-allocated memory, but has the advantage of working correctly across a wide variety of hardware and operating
systems, including large clusters. The __gnu_cxx::new_allocator implements the simple operator new and operator
delete semantics, while __gnu_cxx::malloc_allocator implements much the same thing, only with the C language
functions std::malloc and std::free.
Another approach is to use intelligence within the allocator class to cache allocations. This extra machinery can take a variety
of forms: a bitmap index, an index into an exponentially increasing power-of-two-sized buckets, or simpler fixed-size pooling
cache. The cache is shared among all the containers in the program: when your program’s std::vector gets cut in
half and frees a bunch of its storage, that memory can be reused by the private std::list brought in from a
KDE library that you linked against. And operators new and delete are not always called to pass the memory on, either, which
is a speed bonus. Examples of allocators that use these techniques are __gnu_cxx::bitmap_allocator, __gnu_cxx:
:pool_allocator, and __gnu_cxx::__mt_alloc.
Depending on the implementation techniques used, the underlying operating system, and compilation environment, scaling
caching allocators can be tricky. In particular, order-of-destruction and order-of-creation for memory pools may be difficult to
pin down with certainty, which may create problems when used with plugins or loading and unloading shared objects in memory.
As such, using caching allocators on systems that do not support abi::__cxa_atexit is not recommended.

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Implementation
Interface Design

The only allocator interface that is supported is the standard C++ interface. As such, all STL containers have been adjusted, and
all external allocators have been modified to support this change.
The class allocator just has typedef, constructor, and rebind members. It inherits from one of the high-speed extension
allocators, covered below. Thus, all allocation and deallocation depends on the base class.
The base class that allocator is derived from may not be user-configurable.
6.3.1.3.2

Selecting Default Allocation Policy

It’s difficult to pick an allocation strategy that will provide maximum utility, without excessively penalizing some behavior. In
fact, it’s difficult just deciding which typical actions to measure for speed.
Three synthetic benchmarks have been created that provide data that is used to compare different C++ allocators. These tests are:
1. Insertion.
Over multiple iterations, various STL container objects have elements inserted to some maximum amount. A variety of
allocators are tested. Test source for sequence and associative containers.
2. Insertion and erasure in a multi-threaded environment.
This test shows the ability of the allocator to reclaim memory on a per-thread basis, as well as measuring thread contention
for memory resources. Test source here.
3. A threaded producer/consumer model.
Test source for sequence and associative containers.
The current default choice for allocator is __gnu_cxx::new_allocator.
6.3.1.3.3

Disabling Memory Caching

In use, allocator may allocate and deallocate using implementation-specific strategies and heuristics. Because of this, a given
call to an allocator object’s allocate member function may not actually call the global operator new and a given call to
to the deallocate member function may not call operator delete.
This can be confusing.
In particular, this can make debugging memory errors more difficult, especially when using third-party tools like valgrind or
debug versions of new.
There are various ways to solve this problem. One would be to use a custom allocator that just called operators new and delete
directly, for every allocation. (See the default allocator, include/ext/new_allocator.h, for instance.) However, that
option may involve changing source code to use a non-default allocator. Another option is to force the default allocator to remove
caching and pools, and to directly allocate with every call of allocate and directly deallocate with every call of deallocate,
regardless of efficiency. As it turns out, this last option is also available.
To globally disable memory caching within the library for some of the optional non-default allocators, merely set GLIBCXX_F
ORCE_NEW (with any value) in the system’s environment before running the program. If your program crashes with GLIBCXX
_FORCE_NEW in the environment, it likely means that you linked against objects built against the older library (objects which
might still using the cached allocations...).

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Using a Specific Allocator

You can specify different memory management schemes on a per-container basis, by overriding the default Allocator template
parameter. For example, an easy (but non-portable) method of specifying that only malloc or free should be used instead of
the default node allocator is:
std::list  >

malloc_list;

Likewise, a debugging form of whichever allocator is currently in use:
std::deque  > >

6.3.1.5

debug_deque;

Custom Allocators

Writing a portable C++ allocator would dictate that the interface would look much like the one specified for allocator.
Additional member functions, but not subtractions, would be permissible.
Probably the best place to start would be to copy one of the extension allocators: say a simple one like new_allocator.
6.3.1.6

Extension Allocators

Several other allocators are provided as part of this implementation. The location of the extension allocators and their names have
changed, but in all cases, functionality is equivalent. Starting with gcc-3.4, all extension allocators are standard style. Before this
point, SGI style was the norm. Because of this, the number of template arguments also changed. Here’s a simple chart to track
the changes.
More details on each of these extension allocators follows.
1. new_allocator
Simply wraps ::operator new and ::operator delete.
2. malloc_allocator
Simply wraps malloc and free. There is also a hook for an out-of-memory handler (for new/delete this is taken care
of elsewhere).
3. array_allocator
Allows allocations of known and fixed sizes using existing global or external storage allocated via construction of std:
:tr1::array objects. By using this allocator, fixed size containers (including std::string) can be used without
instances calling ::operator new and ::operator delete. This capability allows the use of STL abstractions
without runtime complications or overhead, even in situations such as program startup. For usage examples, please consult
the testsuite.
4. debug_allocator
A wrapper around an arbitrary allocator A. It passes on slightly increased size requests to A, and uses the extra memory to
store size information. When a pointer is passed to deallocate(), the stored size is checked, and assert() is used
to guarantee they match.
5. throw_allocator
Includes memory tracking and marking abilities as well as hooks for throwing exceptions at configurable intervals (including random, all, none).
6. __pool_alloc
A high-performance, single pool allocator. The reusable memory is shared among identical instantiations of this type. It
calls through ::operator new to obtain new memory when its lists run out. If a client container requests a block larger
than a certain threshold size, then the pool is bypassed, and the allocate/deallocate request is passed to ::operator new
directly.

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Older versions of this class take a boolean template parameter, called thr, and an integer template parameter, called inst.
The inst number is used to track additional memory pools. The point of the number is to allow multiple instantiations of
the classes without changing the semantics at all. All three of
typedef
typedef
typedef

__pool_alloc
__pool_alloc
__pool_alloc

normal;
private;
also_private;

behave exactly the same way. However, the memory pool for each type (and remember that different instantiations result
in different types) remains separate.
The library uses 0 in all its instantiations. If you wish to keep separate free lists for a particular purpose, use a different
number.
The thr boolean determines whether the pool should be manipulated atomically or not. When thr = true, the allocator
is thread-safe, while thr = false, is slightly faster but unsafe for multiple threads.
For thread-enabled configurations, the pool is locked with a single big lock. In some situations, this implementation detail
may result in severe performance degradation.
(Note that the GCC thread abstraction layer allows us to provide safe zero-overhead stubs for the threading routines, if
threads were disabled at configuration time.)
7. __mt_alloc
A high-performance fixed-size allocator with exponentially-increasing allocations. It has its own chapter in the documentation.
8. bitmap_allocator
A high-performance allocator that uses a bit-map to keep track of the used and unused memory locations. It has its own
chapter in the documentation.
6.3.1.7

Bibliography

[9] Matt Austern, The Standard Librarian: What Are Allocators Good For? , C/C++ Users Journal .
[10] Emery Berger, The Hoard Memory Allocator
[11] Emery BergerBen ZornKathryn McKinley, Reconsidering Custom Memory Allocation , Copyright © 2002
OOPSLA.
[12] Klaus KreftAngelika Langer, Allocator Types , C/C++ Users Journal .
[13] Bjarne Stroustrup, Copyright © 2000 , 19.4 Allocators, Addison Wesley .
[14] Felix Yen
[isoc++_1998]

, 20.4 Memory.

6.3.2

auto_ptr

6.3.2.1

Limitations

Explaining all of the fun and delicious things that can happen with misuse of the auto_ptr class template (called AP here)
would take some time. Suffice it to say that the use of AP safely in the presence of copying has some subtleties.
The AP class is a really nifty idea for a smart pointer, but it is one of the dumbest of all the smart pointers -- and that’s fine.
AP is not meant to be a supersmart solution to all resource leaks everywhere. Neither is it meant to be an effective form of
garbage collection (although it can help, a little bit). And it can notbe used for arrays!
AP is meant to prevent nasty leaks in the presence of exceptions. That’s all. This code is AP-friendly:

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// Not a recommend naming scheme, but good for web-based FAQs.
typedef std::auto_ptr APMC;
extern function_taking_MyClass_pointer (MyClass*);
extern some_throwable_function ();
void func (int data)
{
APMC ap (new MyClass(data));
some_throwable_function();

// this will throw an exception

function_taking_MyClass_pointer (ap.get());
}

When an exception gets thrown, the instance of MyClass that’s been created on the heap will be delete’d as the stack is
unwound past func().
Changing that code as follows is not AP-friendly:
APMC

ap (new MyClass[22]);

You will get the same problems as you would without the use of AP:
char* array = new char[10];
...
delete array;

// array new...
// ...but single-object delete

AP cannot tell whether the pointer you’ve passed at creation points to one or many things. If it points to many things, you are
about to die. AP is trivial to write, however, so you could write your own auto_array_ptr for that situation (in fact, this has
been done many times; check the mailing lists, Usenet, Boost, etc).
6.3.2.2

Use in Containers

All of the containers described in the standard library require their contained types to have, among other things, a copy constructor
like this:
struct My_Type
{
My_Type (My_Type const&);
};

Note the const keyword; the object being copied shouldn’t change. The template class auto_ptr (called AP here) does not
meet this requirement. Creating a new AP by copying an existing one transfers ownership of the pointed-to object, which means
that the AP being copied must change, which in turn means that the copy ctors of AP do not take const objects.
The resulting rule is simple: Never ever use a container of auto_ptr objects. The standard says that “undefined” behavior is the
result, but it is guaranteed to be messy.
To prevent you from doing this to yourself, the concept checks built in to this implementation will issue an error if you try to
compile code like this:
#include 
#include 
void f()
{
std::vector< std::auto_ptr >
}

vec_ap_int;

Should you try this with the checks enabled, you will see an error.

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shared_ptr

The shared_ptr class template stores a pointer, usually obtained via new, and implements shared ownership semantics.
6.3.3.1

Requirements

The standard deliberately doesn’t require a reference-counted implementation, allowing other techniques such as a circularlinked-list.
6.3.3.2

Design Issues

The shared_ptr code is kindly donated to GCC by the Boost project and the original authors of the code. The basic design
and algorithms are from Boost, the notes below describe details specific to the GCC implementation. Names have been uglified
in this implementation, but the design should be recognisable to anyone familiar with the Boost 1.32 shared_ptr.
The basic design is an abstract base class, _Sp_counted_base that does the reference-counting and calls virtual functions
when the count drops to zero. Derived classes override those functions to destroy resources in a context where the correct
dynamic type is known. This is an application of the technique known as type erasure.
6.3.3.3
6.3.3.3.1

Implementation
Class Hierarchy

A shared_ptr contains a pointer of type T* and an object of type __shared_count. The shared_count contains a
pointer of type _Sp_counted_base* which points to the object that maintains the reference-counts and destroys the managed
resource.
_Sp_counted_base The base of the hierarchy is parameterized on the lock policy (see below.) _Sp_counted_base
doesn’t depend on the type of pointer being managed, it only maintains the reference counts and calls virtual functions when the counts drop to zero. The managed object is destroyed when the last strong reference is dropped, but
the _Sp_counted_base itself must exist until the last weak reference is dropped.
_Sp_counted_base_impl Inherits from _Sp_counted_base and stores a pointer of type Ptr
and a deleter of type Deleter. _Sp_deleter is used when the user doesn’t supply a custom deleter. Unlike Boost’s,
this default deleter is not "checked" because GCC already issues a warning if delete is used with an incomplete type.
This is the only derived type used by tr1::shared_ptr and it is never used by std::shared_ptr, which
uses one of the following types, depending on how the shared_ptr is constructed.
_Sp_counted_ptr Inherits from _Sp_counted_base and stores a pointer of type Ptr, which is passed to delete
when the last reference is dropped. This is the simplest form and is used when there is no custom deleter or allocator.
_Sp_counted_deleter Inherits from _Sp_counted_ptr and adds support for custom deleter
and allocator. Empty Base Optimization is used for the allocator. This class is used even when the user only provides a
custom deleter, in which case allocator is used as the allocator.
_Sp_counted_ptr_inplace Used by allocate_shared and make_shared. Contains aligned
storage to hold an object of type Tp, which is constructed in-place with placement new. Has a variadic template constructor allowing any number of arguments to be forwarded to Tp’s constructor. Unlike the other _Sp_counted_* classes,
this one is parameterized on the type of object, not the type of pointer; this is purely a convenience that simplifies the
implementation slightly.
C++11-only features are: rvalue-ref/move support, allocator support, aliasing constructor, make_shared & allocate_shared. Additionally, the constructors taking auto_ptr parameters are deprecated in C++11 mode.

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Thread Safety

The Thread Safety section of the Boost shared_ptr documentation says "shared_ptr objects offer the same level of thread safety as
built-in types." The implementation must ensure that concurrent updates to separate shared_ptr instances are correct even when
those instances share a reference count e.g.
shared_ptr a(new A);
shared_ptr b(a);
// Thread 1
a.reset();

// Thread 2
b.reset();

The dynamically-allocated object must be destroyed by exactly one of the threads. Weak references make things even more
interesting. The shared state used to implement shared_ptr must be transparent to the user and invariants must be preserved at
all times. The key pieces of shared state are the strong and weak reference counts. Updates to these need to be atomic and
visible to all threads to ensure correct cleanup of the managed resource (which is, after all, shared_ptr’s job!) On multi-processor
systems memory synchronisation may be needed so that reference-count updates and the destruction of the managed resource
are race-free.
The function _Sp_counted_base::_M_add_ref_lock(), called when obtaining a shared_ptr from a weak_ptr, has to
test if the managed resource still exists and either increment the reference count or throw bad_weak_ptr. In a multi-threaded
program there is a potential race condition if the last reference is dropped (and the managed resource destroyed) between testing
the reference count and incrementing it, which could result in a shared_ptr pointing to invalid memory.
The Boost shared_ptr (as used in GCC) features a clever lock-free algorithm to avoid the race condition, but this relies on the
processor supporting an atomic Compare-And-Swap instruction. For other platforms there are fall-backs using mutex locks.
Boost (as of version 1.35) includes several different implementations and the preprocessor selects one based on the compiler,
standard library, platform etc. For the version of shared_ptr in libstdc++ the compiler and library are fixed, which makes things
much simpler: we have an atomic CAS or we don’t, see Lock Policy below for details.
6.3.3.3.3

Selecting Lock Policy

There is a single _Sp_counted_base class, which is a template parameterized on the enum __gnu_cxx::_Lock_policy. The
entire family of classes is parameterized on the lock policy, right up to __shared_ptr, __weak_ptr and __enable_s
hared_from_this. The actual std::shared_ptr class inherits from __shared_ptr with the lock policy parameter
selected automatically based on the thread model and platform that libstdc++ is configured for, so that the best available template
specialization will be used. This design is necessary because it would not be conforming for shared_ptr to have an extra
template parameter, even if it had a default value. The available policies are:
1. _S_Atomic
Selected when GCC supports a builtin atomic compare-and-swap operation on the target processor (see Atomic Builtins.)
The reference counts are maintained using a lock-free algorithm and GCC’s atomic builtins, which provide the required
memory synchronisation.
2. _S_Mutex
The _Sp_counted_base specialization for this policy contains a mutex, which is locked in add_ref_lock(). This policy is
used when GCC’s atomic builtins aren’t available so explicit memory barriers are needed in places.
3. _S_Single
This policy uses a non-reentrant add_ref_lock() with no locking. It is used when libstdc++ is built without --enablethreads.
For all three policies, reference count increments and decrements are done via the functions in ext/atomicity.h, which
detect if the program is multi-threaded. If only one thread of execution exists in the program then less expensive non-atomic
operations are used.

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Related functions and classes

dynamic_pointer_cast, static_pointer_cast, const_pointer_cast As noted in N2351, these functions can
be implemented non-intrusively using the alias constructor. However the aliasing constructor is only available in C++11
mode, so in TR1 mode these casts rely on three non-standard constructors in shared_ptr and __shared_ptr. In C++11 mode
these constructors and the related tag types are not needed.
enable_shared_from_this The clever overload to detect a base class of type enable_shared_from_this comes
straight from Boost. There is an extra overload for __enable_shared_from_this to work smoothly with __shar
ed_ptr using any lock policy.
make_shared, allocate_shared make_shared simply forwards to allocate_shared with std::allocator
as the allocator. Although these functions can be implemented non-intrusively using the alias constructor, if they have
access to the implementation then it is possible to save storage and reduce the number of heap allocations. The newly
constructed object and the _Sp_counted_* can be allocated in a single block and the standard says implementations are
"encouraged, but not required," to do so. This implementation provides additional non-standard constructors (selected with
the type _Sp_make_shared_tag) which create an object of type _Sp_counted_ptr_inplace to hold the new
object. The returned shared_ptr needs to know the address of the new A object embedded in the _Sp_counte
d_ptr_inplace, but it has no way to access it. This implementation uses a "covert channel" to return the address of
the embedded object when get_deleter<_Sp_make_shared_tag>() is called. Users should not try to use this.
As well as the extra constructors, this implementation also needs some members of _Sp_counted_deleter to be protected
where they could otherwise be private.
6.3.3.4
6.3.3.4.1

Use
Examples

Examples of use can be found in the testsuite, under testsuite/tr1/2_general_utilities/shared_ptr, testsuite/
20_util/shared_ptr and testsuite/20_util/weak_ptr.
6.3.3.4.2

Unresolved Issues

The shared_ptr atomic access clause in the C++11 standard is not implemented in GCC.
Unlike Boost, this implementation does not use separate classes for the pointer+deleter and pointer+deleter+allocator cases in
C++11 mode, combining both into _Sp_counted_deleter and using allocator when the user doesn’t specify an allocator. If it
was found to be beneficial an additional class could easily be added. With the current implementation, the _Sp_counted_deleter
and __shared_count constructors taking a custom deleter but no allocator are technically redundant and could be removed,
changing callers to always specify an allocator. If a separate pointer+deleter class was added the __shared_count constructor
would be needed, so it has been kept for now.
The hack used to get the address of the managed object from _Sp_counted_ptr_inplace::_M_get_deleter() is
accessible to users. This could be prevented if get_deleter<_Sp_make_shared_tag>() always returned NULL, since
the hack only needs to work at a lower level, not in the public API. This wouldn’t be difficult, but hasn’t been done since there
is no danger of accidental misuse: users already know they are relying on unsupported features if they refer to implementation
details such as _Sp_make_shared_tag.
tr1::_Sp_deleter could be a private member of tr1::__shared_count but it would alter the ABI.
6.3.3.5

Acknowledgments

The original authors of the Boost shared_ptr, which is really nice code to work with, Peter Dimov in particular for his help and
invaluable advice on thread safety. Phillip Jordan and Paolo Carlini for the lock policy implementation.

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6.3.3.6

Bibliography

[15] Improving shared_ptr for C++0x, Revision 2 , N2351 .
[16] C++ Standard Library Active Issues List , N2456 .
[17] Working Draft, Standard for Programming Language C++ , N2461 .
[18] Boost C++ Libraries documentation, shared_ptr , N2461 .

6.4

Traits

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Chapter 7

Strings
7.1
7.1.1

String Classes
Simple Transformations

Here are Standard, simple, and portable ways to perform common transformations on a string instance, such as "convert to all
upper case." The word transformations is especially apt, because the standard template function transform<> is used.
This code will go through some iterations. Here’s a simple version:
#include 
#include 
#include 

// old 

struct ToLower
{
char operator() (char c) const
};
struct ToUpper
{
char operator() (char c) const
};
int main()
{
std::string

{ return std::tolower(c); }

{ return std::toupper(c); }

s ("Some Kind Of Initial Input Goes Here");

// Change everything into upper case
std::transform (s.begin(), s.end(), s.begin(), ToUpper());
// Change everything into lower case
std::transform (s.begin(), s.end(), s.begin(), ToLower());
// Change everything back into upper case, but store the
// result in a different string
std::string capital_s;
capital_s.resize(s.size());
std::transform (s.begin(), s.end(), capital_s.begin(), ToUpper());
}

Note that these calls all involve the global C locale through the use of the C functions toupper/tolower. This is absolutely
guaranteed to work -- but only if the string contains only characters from the basic source character set, and there are only 96 of

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those. Which means that not even all English text can be represented (certain British spellings, proper names, and so forth). So,
if all your input forevermore consists of only those 96 characters (hahahahahaha), then you’re done.
Note that the ToUpper and ToLower function objects are needed because toupper and tolower are overloaded names
(declared in  and ) so the template-arguments for transform<> cannot be deduced, as explained in
this message. At minimum, you can write short wrappers like
char toLower (char c)
{
return std::tolower(c);
}

(Thanks to James Kanze for assistance and suggestions on all of this.)
Another common operation is trimming off excess whitespace. Much like transformations, this task is trivial with the use of
string’s find family. These examples are broken into multiple statements for readability:
std::string

str (" \t blah blah blah

\n ");

// trim leading whitespace
string::size_type notwhite = str.find_first_not_of(" \t\n");
str.erase(0,notwhite);
// trim trailing whitespace
notwhite = str.find_last_not_of(" \t\n");
str.erase(notwhite+1);

Obviously, the calls to find could be inserted directly into the calls to erase, in case your compiler does not optimize named
temporaries out of existence.

7.1.2

Case Sensitivity

The well-known-and-if-it-isn’t-well-known-it-ought-to-be Guru of the Week discussions held on Usenet covered this topic in
January of 1998. Briefly, the challenge was, “write a ’ci_string’ class which is identical to the standard ’string’ class, but is
case-insensitive in the same way as the (common but nonstandard) C function stricmp()”.
ci_string s( "AbCdE" );
// case insensitive
assert( s == "abcde" );
assert( s == "ABCDE" );
// still case-preserving, of course
assert( strcmp( s.c_str(), "AbCdE" ) == 0 );
assert( strcmp( s.c_str(), "abcde" ) != 0 );

The solution is surprisingly easy. The original answer was posted on Usenet, and a revised version appears in Herb Sutter’s book
Exceptional C++ and on his website as GotW 29.
See? Told you it was easy!
Added June 2000: The May 2000 issue of C++ Report contains a fascinating article by Matt Austern (yes, the Matt Austern)
on why case-insensitive comparisons are not as easy as they seem, and why creating a class is the wrong way to go about it in
production code. (The GotW answer mentions one of the principle difficulties; his article mentions more.)
Basically, this is "easy" only if you ignore some things, things which may be too important to your program to ignore. (I chose
to ignore them when originally writing this entry, and am surprised that nobody ever called me on it...) The GotW question and
answer remain useful instructional tools, however.
Added September 2000: James Kanze provided a link to a Unicode Technical Report discussing case handling, which provides
some very good information.

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Arbitrary Character Types

The std::basic_string is tantalizingly general, in that it is parameterized on the type of the characters which it holds.
In theory, you could whip up a Unicode character class and instantiate std::basic_string, or
assuming that integers are wider than characters on your platform, maybe just declare variables of type std::basic_strin
g.
That’s the theory. Remember however that basic_string has additional type parameters, which take default arguments based on
the character type (called CharT here):
template ,
typename Alloc = allocator >
class basic_string { .... };

Now, allocator will probably Do The Right Thing by default, unless you need to implement your own allocator
for your characters.
But char_traits takes more work. The char_traits template is declared but not defined. That means there is only
template 
struct char_traits
{
static void foo (type1 x, type2 y);
...
};

and functions such as char_traits::foo() are not actually defined anywhere for the general case. The C++ standard
permits this, because writing such a definition to fit all possible CharT’s cannot be done.
The C++ standard also requires that char_traits be specialized for instantiations of char and wchar_t, and it is these template
specializations that permit entities like basic_string> to work.
If you want to use character types other than char and wchar_t, such as unsigned char and int, you will need suitable
specializations for them. For a time, in earlier versions of GCC, there was a mostly-correct implementation that let programmers
be lazy but it broke under many situations, so it was removed. GCC 3.4 introduced a new implementation that mostly works and
can be specialized even for int and other built-in types.
If you want to use your own special character class, then you have a lot of work to do, especially if you with to use i18n features
(facets require traits information but don’t have a traits argument).
Another example of how to specialize char_traits was given on the mailing list and at a later date was put into the file include/
ext/pod_char_traits.h. We agree that the way it’s used with basic_string (scroll down to main()) doesn’t look nice, but
that’s because the nice-looking first attempt turned out to not be conforming C++, due to the rule that CharT must be a POD.
(See how tricky this is?)

7.1.4

Tokenizing

The Standard C (and C++) function strtok() leaves a lot to be desired in terms of user-friendliness. It’s unintuitive, it destroys
the character string on which it operates, and it requires you to handle all the memory problems. But it does let the client code
decide what to use to break the string into pieces; it allows you to choose the "whitespace," so to speak.
A C++ implementation lets us keep the good things and fix those annoyances. The implementation here is more intuitive (you
only call it once, not in a loop with varying argument), it does not affect the original string at all, and all the memory allocation
is handled for you.
It’s called stringtok, and it’s a template function. Sources are as below, in a less-portable form than it could be, to keep this
example simple (for example, see the comments on what kind of string it will accept).
#include 
template 
void

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stringtok(Container &container, string const &in,
const char * const delimiters = " \t\n")
{
const string::size_type len = in.length();
string::size_type i = 0;
while (i < len)
{
// Eat leading whitespace
i = in.find_first_not_of(delimiters, i);
if (i == string::npos)
return;
// Nothing left but white space
// Find the end of the token
string::size_type j = in.find_first_of(delimiters, i);
// Push token
if (j == string::npos)
{
container.push_back(in.substr(i));
return;
}
else
container.push_back(in.substr(i, j-i));
// Set up for next loop
i = j + 1;
}
}

The author uses a more general (but less readable) form of it for parsing command strings and the like. If you compiled and ran
this code using it:
std::list ls;
stringtok (ls, " this \t is\t\n a test ");
for (std::listconst_iterator i = ls.begin();
i != ls.end(); ++i)
{
std::cerr << ’:’ << (*i) << ":\n";
}

You would see this as output:
:this:
:is:
:a:
:test:

with all the whitespace removed. The original s is still available for use, ls will clean up after itself, and ls.size() will
return how many tokens there were.
As always, there is a price paid here, in that stringtok is not as fast as strtok. The other benefits usually outweigh that, however.
Added February 2001: Mark Wilden pointed out that the standard std::getline() function can be used with standard
istringstreams to perform tokenizing as well. Build an istringstream from the input text, and then use std::getline with
varying delimiters (the three-argument signature) to extract tokens into a string.

7.1.5

Shrink to Fit

From GCC 3.4 calling s.reserve(res) on a string s with res < s.capacity() will reduce the string’s capacity
to std::max(s.size(), res).

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This behaviour is suggested, but not required by the standard. Prior to GCC 3.4 the following alternative can be used instead
std::string(str.data(), str.size()).swap(str);

This is similar to the idiom for reducing a vector’s memory usage (see this FAQ entry) but the regular copy constructor cannot
be used because libstdc++’s string is Copy-On-Write in GCC 3.
In C++11 mode you can call s.shrink_to_fit() to achieve the same effect as s.reserve(s.size()).

7.1.6

CString (MFC)

A common lament seen in various newsgroups deals with the Standard string class as opposed to the Microsoft Foundation Class
called CString. Often programmers realize that a standard portable answer is better than a proprietary nonportable one, but in
porting their application from a Win32 platform, they discover that they are relying on special functions offered by the CString
class.
Things are not as bad as they seem. In this message, Joe Buck points out a few very important things:
• The Standard string supports all the operations that CString does, with three exceptions.
• Two of those exceptions (whitespace trimming and case conversion) are trivial to implement. In fact, we do so on this page.
• The third is CString::Format, which allows formatting in the style of sprintf. This deserves some mention:
The old libg++ library had a function called form(), which did much the same thing. But for a Standard solution, you should use
the stringstream classes. These are the bridge between the iostream hierarchy and the string class, and they operate with regular
streams seamlessly because they inherit from the iostream hierarchy. An quick example:
#include 
#include 
#include 
string f (string& incoming)
// incoming is "foo
{
istringstream
incoming_stream(incoming);
string
the_word;
int
the_number;

N"

incoming_stream >> the_word
// extract "foo"
>> the_number;
// extract N
ostringstream
output_stream;
output_stream << "The word was " << the_word
<< " and 3*N was " << (3*the_number);
return output_stream.str();
}

A serious problem with CString is a design bug in its memory allocation. Specifically, quoting from that same message:
CString suffers from a common programming error that results in
poor performance. Consider the following code:
CString n_copies_of (const CString& foo, unsigned n)
{
CString tmp;
for (unsigned i = 0; i < n; i++)
tmp += foo;
return tmp;
}

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This function is O(n^2), not O(n). The reason is that each +=
causes a reallocation and copy of the existing string. Microsoft
applications are full of this kind of thing (quadratic performance
on tasks that can be done in linear time) -- on the other hand,
we should be thankful, as it’s created such a big market for high-end
ix86 hardware. :-)
If you replace CString with string in the above function, the
performance is O(n).

Joe Buck also pointed out some other things to keep in mind when comparing CString and the Standard string class:
• CString permits access to its internal representation; coders who exploited that may have problems moving to string.
• Microsoft ships the source to CString (in the files MFC\SRC\Str{core,ex}.cpp), so you could fix the allocation bug and rebuild
your MFC libraries. Note: It looks like the CString shipped with VC++6.0 has fixed this, although it may in fact have been one
of the VC++ SPs that did it.
• string operations like this have O(n) complexity if the implementors do it correctly. The libstdc++ implementors did it
correctly. Other vendors might not.
• While parts of the SGI STL are used in libstdc++, their string class is not. The SGI string is essentially vector
and does not do any reference counting like libstdc++’s does. (It is O(n), though.) So if you’re thinking about SGI’s string or
rope classes, you’re now looking at four possibilities: CString, the libstdc++ string, the SGI string, and the SGI rope, and this
is all before any allocator or traits customizations! (More choices than you can shake a stick at -- want fries with that?)

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Chapter 8

Localization
8.1

Locales

8.1.1

locale

Describes the basic locale object, including nested classes id, facet, and the reference-counted implementation object, class
_Impl.
8.1.1.1

Requirements

Class locale is non-templatized and has two distinct types nested inside of it:
class facet 22.1.1.1.2 Class locale::facet
Facets actually implement locale functionality. For instance, a facet called numpunct is the data object that can be used to query
for the thousands separator in the locale.
Literally, a facet is strictly defined:
• Containing the following public data member:
static locale::id id;
• Derived from another facet:
class gnu_codecvt:public std::ctype
Of interest in this class are the memory management options explicitly specified as an argument to facet’s constructor. Each
constructor of a facet class takes a std::size_t __refs argument: if __refs == 0, the facet is deleted when the locale containing it is
destroyed. If __refs == 1, the facet is not destroyed, even when it is no longer referenced.
class id 22.1.1.1.3 - Class locale::id
Provides an index for looking up specific facets.
8.1.1.2

Design

The major design challenge is fitting an object-orientated and non-global locale design on top of POSIX and other relevant
standards, which include the Single Unix (nee X/Open.)
Because C and earlier versions of POSIX fall down so completely, portability is an issue.

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8.1.1.3

Implementation

8.1.1.3.1

Interacting with "C" locales

• locale -a displays available locales.
af_ZA
ar_AE
ar_AE.utf8
ar_BH
ar_BH.utf8
ar_DZ
ar_DZ.utf8
ar_EG
ar_EG.utf8
ar_IN
ar_IQ
ar_IQ.utf8
ar_JO
ar_JO.utf8
ar_KW
ar_KW.utf8
ar_LB
ar_LB.utf8
ar_LY
ar_LY.utf8
ar_MA
ar_MA.utf8
ar_OM
ar_OM.utf8
ar_QA
ar_QA.utf8
ar_SA
ar_SA.utf8
ar_SD
ar_SD.utf8
ar_SY
ar_SY.utf8
ar_TN
ar_TN.utf8
ar_YE
ar_YE.utf8
be_BY
be_BY.utf8
bg_BG
bg_BG.utf8
br_FR
bs_BA
C
ca_ES
ca_ES@euro
ca_ES.utf8
ca_ES.utf8@euro
cs_CZ
cs_CZ.utf8
cy_GB
da_DK
da_DK.iso885915
da_DK.utf8
de_AT
de_AT@euro

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de_AT.utf8
de_AT.utf8@euro
de_BE
de_BE@euro
de_BE.utf8
de_BE.utf8@euro
de_CH
de_CH.utf8
de_DE
de_DE@euro
de_DE.utf8
de_DE.utf8@euro
de_LU
de_LU@euro
de_LU.utf8
de_LU.utf8@euro
el_GR
el_GR.utf8
en_AU
en_AU.utf8
en_BW
en_BW.utf8
en_CA
en_CA.utf8
en_DK
en_DK.utf8
en_GB
en_GB.iso885915
en_GB.utf8
en_HK
en_HK.utf8
en_IE
en_IE@euro
en_IE.utf8
en_IE.utf8@euro
en_IN
en_NZ
en_NZ.utf8
en_PH
en_PH.utf8
en_SG
en_SG.utf8
en_US
en_US.iso885915
en_US.utf8
en_ZA
en_ZA.utf8
en_ZW
en_ZW.utf8
es_AR
es_AR.utf8
es_BO
es_BO.utf8
es_CL
es_CL.utf8
es_CO
es_CO.utf8
es_CR
es_CR.utf8
es_DO
es_DO.utf8
es_EC

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es_EC.utf8
es_ES
es_ES@euro
es_ES.utf8
es_ES.utf8@euro
es_GT
es_GT.utf8
es_HN
es_HN.utf8
es_MX
es_MX.utf8
es_NI
es_NI.utf8
es_PA
es_PA.utf8
es_PE
es_PE.utf8
es_PR
es_PR.utf8
es_PY
es_PY.utf8
es_SV
es_SV.utf8
es_US
es_US.utf8
es_UY
es_UY.utf8
es_VE
es_VE.utf8
et_EE
et_EE.utf8
eu_ES
eu_ES@euro
eu_ES.utf8
eu_ES.utf8@euro
fa_IR
fi_FI
fi_FI@euro
fi_FI.utf8
fi_FI.utf8@euro
fo_FO
fo_FO.utf8
fr_BE
fr_BE@euro
fr_BE.utf8
fr_BE.utf8@euro
fr_CA
fr_CA.utf8
fr_CH
fr_CH.utf8
fr_FR
fr_FR@euro
fr_FR.utf8
fr_FR.utf8@euro
fr_LU
fr_LU@euro
fr_LU.utf8
fr_LU.utf8@euro
ga_IE
ga_IE@euro
ga_IE.utf8
ga_IE.utf8@euro

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gl_ES
gl_ES@euro
gl_ES.utf8
gl_ES.utf8@euro
gv_GB
gv_GB.utf8
he_IL
he_IL.utf8
hi_IN
hr_HR
hr_HR.utf8
hu_HU
hu_HU.utf8
id_ID
id_ID.utf8
is_IS
is_IS.utf8
it_CH
it_CH.utf8
it_IT
it_IT@euro
it_IT.utf8
it_IT.utf8@euro
iw_IL
iw_IL.utf8
ja_JP.eucjp
ja_JP.utf8
ka_GE
kl_GL
kl_GL.utf8
ko_KR.euckr
ko_KR.utf8
kw_GB
kw_GB.utf8
lt_LT
lt_LT.utf8
lv_LV
lv_LV.utf8
mi_NZ
mk_MK
mk_MK.utf8
mr_IN
ms_MY
ms_MY.utf8
mt_MT
mt_MT.utf8
nl_BE
nl_BE@euro
nl_BE.utf8
nl_BE.utf8@euro
nl_NL
nl_NL@euro
nl_NL.utf8
nl_NL.utf8@euro
nn_NO
nn_NO.utf8
no_NO
no_NO.utf8
oc_FR
pl_PL
pl_PL.utf8
POSIX

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pt_BR
pt_BR.utf8
pt_PT
pt_PT@euro
pt_PT.utf8
pt_PT.utf8@euro
ro_RO
ro_RO.utf8
ru_RU
ru_RU.koi8r
ru_RU.utf8
ru_UA
ru_UA.utf8
se_NO
sk_SK
sk_SK.utf8
sl_SI
sl_SI.utf8
sq_AL
sq_AL.utf8
sr_YU
sr_YU@cyrillic
sr_YU.utf8
sr_YU.utf8@cyrillic
sv_FI
sv_FI@euro
sv_FI.utf8
sv_FI.utf8@euro
sv_SE
sv_SE.iso885915
sv_SE.utf8
ta_IN
te_IN
tg_TJ
th_TH
th_TH.utf8
tl_PH
tr_TR
tr_TR.utf8
uk_UA
uk_UA.utf8
ur_PK
uz_UZ
vi_VN
vi_VN.tcvn
wa_BE
wa_BE@euro
yi_US
zh_CN
zh_CN.gb18030
zh_CN.gbk
zh_CN.utf8
zh_HK
zh_HK.utf8
zh_TW
zh_TW.euctw
zh_TW.utf8

• `locale` displays environmental variables that impact how locale("") will be deduced.
LANG=en_US

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LC_CTYPE="en_US"
LC_NUMERIC="en_US"
LC_TIME="en_US"
LC_COLLATE="en_US"
LC_MONETARY="en_US"
LC_MESSAGES="en_US"
LC_PAPER="en_US"
LC_NAME="en_US"
LC_ADDRESS="en_US"
LC_TELEPHONE="en_US"
LC_MEASUREMENT="en_US"
LC_IDENTIFICATION="en_US"
LC_ALL=

From Josuttis, p. 697-698, which says, that "there is only *one* relation (of the C++ locale mechanism) to the C locale mechanism: the global C locale is modified if a named C++ locale object is set as the global locale" (emphasis Paolo), that is:
std::locale::global(std::locale(""));

affects the C functions as if the following call was made:
std::setlocale(LC_ALL, "");

On the other hand, there is *no* vice versa, that is, calling setlocale has *no* whatsoever on the C++ locale mechanism, in
particular on the working of locale(""), which constructs the locale object from the environment of the running program, that is,
in practice, the set of LC_ALL, LANG, etc. variable of the shell.
8.1.1.4

Future

• Locale initialization: at what point does _S_classic, _S_global get initialized? Can named locales assume this initialization
has already taken place?
• Document how named locales error check when filling data members. I.e., a fr_FR locale that doesn’t have numpunct::truename():
does it use "true"? Or is it a blank string? What’s the convention?
• Explain how locale aliasing happens. When does "de_DE" use "de" information? What is the rule for locales composed of just
an ISO language code (say, "de") and locales with both an ISO language code and ISO country code (say, "de_DE").
• What should non-required facet instantiations do? If the generic implementation is provided, then how to end-users provide
specializations?
8.1.1.5

Bibliography

[19] Roland McGrathUlrich Drepper, Copyright © 2007 FSF, Chapters 6 Character Set Handling and 7 Locales and
Internationalization .
[20] Ulrich Drepper, Copyright © 2002 .
[21] , Copyright © 1998 ISO.
[22] , Copyright © 1999 ISO.
[23] System Interface Definitions, Issue 7 (IEEE Std. 1003.1-2008) , Copyright © 2008 The Open Group/The
Institute of Electrical and Electronics Engineers, Inc. .
[24] Bjarne Stroustrup, Copyright © 2000 Addison Wesley, Inc., Appendix D, Addison Wesley .
[25] Angelika LangerKlaus Kreft, Advanced Programmer’s Guide and Reference , Copyright © 2000 Addison Wesley Longman, Inc., Addison Wesley Longman .

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8.2

Facets

8.2.1

ctype

8.2.1.1

Implementation

8.2.1.1.1

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Specializations

For the required specialization codecvt, conversions are made between the internal
character set (always UCS4 on GNU/Linux) and whatever the currently selected locale for the LC_CTYPE category implements.
The two required specializations are implemented as follows:
ctype
This is simple specialization. Implementing this was a piece of cake.
ctype
This specialization, by specifying all the template parameters, pretty much ties the hands of implementors. As such, the implementation is straightforward, involving mcsrtombs for the conversions between char to wchar_t and wcsrtombs for
conversions between wchar_t and char.
Neither of these two required specializations deals with Unicode characters.
8.2.1.2

Future

• How to deal with the global locale issue?
• How to deal with types other than char, wchar_t?
• Overlap between codecvt/ctype: narrow/widen
• mask typedef in codecvt_base, argument types in codecvt. what is know about this type?
• Why mask* argument in codecvt?
• Can this be made (more) generic? is there a simple way to straighten out the configure-time mess that is a by-product of this
class?
• Get the ctype::mask stuff under control. Need to make some kind of static table, and not do lookup every time
somebody hits the do_is... functions. Too bad we can’t just redefine mask for ctype
• Rename abstract base class. See if just smash-overriding is a better approach. Clarify, add sanity to naming.
8.2.1.3

Bibliography

[26] Roland McGrathUlrich Drepper, Copyright © 2007 FSF, Chapters 6 Character Set Handling and 7 Locales and
Internationalization.
[27] Ulrich Drepper, Copyright © 2002 .
[28] , Copyright © 1998 ISO.
[29] , Copyright © 1999 ISO.
[30] The Open Group Base Specifications, Issue 6 (IEEE Std. 1003.1-2004) , Copyright © 1999 The Open
Group/The Institute of Electrical and Electronics Engineers, Inc..
[31] Bjarne Stroustrup, Copyright © 2000 Addison Wesley, Inc., Appendix D, Addison Wesley .
[32] Angelika LangerKlaus Kreft, Advanced Programmer’s Guide and Reference , Copyright © 2000 Addison Wesley Longman, Inc., Addison Wesley Longman .

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8.2.2

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codecvt

The standard class codecvt attempts to address conversions between different character encoding schemes. In particular, the
standard attempts to detail conversions between the implementation-defined wide characters (hereafter referred to as wchar_t)
and the standard type char that is so beloved in classic “C” (which can now be referred to as narrow characters.) This document
attempts to describe how the GNU libstdc++ implementation deals with the conversion between wide and narrow characters, and
also presents a framework for dealing with the huge number of other encodings that iconv can convert, including Unicode and
UTF8. Design issues and requirements are addressed, and examples of correct usage for both the required specializations for
wide and narrow characters and the implementation-provided extended functionality are given.
8.2.2.1

Requirements

Around page 425 of the C++ Standard, this charming heading comes into view:
22.2.1.5 - Template class codecvt
The text around the codecvt definition gives some clues:
-1- The class codecvt is for use when converting from one codeset to another,
such as from wide characters to multibyte characters, between wide character encodings such as Unicode and EUC.
Hmm. So, in some unspecified way, Unicode encodings and translations between other character sets should be handled by this
class.
-2- The stateT argument selects the pair of codesets being mapped between.
Ah ha! Another clue...
-3- The instantiations required in the Table 51 (lib.locale.category), namely codecvt and codecvt, convert the implementation-defined native character
set. codecvt implements a degenerate conversion; it does not convert at all.
codecvt converts between the native character sets for tiny and wide characters. Instantiations on mbstate_t perform conversion between encodings known to the library implementor. Other
encodings can be converted by specializing on a user-defined stateT type. The stateT object can contain any state
that is useful to communicate to or from the specialized do_convert member.
At this point, a couple points become clear:
One: The standard clearly implies that attempts to add non-required (yet useful and widely used) conversions need to do so
through the third template parameter, stateT.
Two: The required conversions, by specifying mbstate_t as the third template parameter, imply an implementation strategy that
is mostly (or wholly) based on the underlying C library, and the functions mcsrtombs and wcsrtombs in particular.
8.2.2.2
8.2.2.2.1

Design
wchar_t Size

The simple implementation detail of wchar_t’s size seems to repeatedly confound people. Many systems use a two byte, unsigned
integral type to represent wide characters, and use an internal encoding of Unicode or UCS2. (See AIX, Microsoft NT, Java,
others.) Other systems, use a four byte, unsigned integral type to represent wide characters, and use an internal encoding of
UCS4. (GNU/Linux systems using glibc, in particular.) The C programming language (and thus C++) does not specify a specific
size for the type wchar_t.
Thus, portable C++ code cannot assume a byte size (or endianness) either.

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Support for Unicode

Probably the most frequently asked question about code conversion is: "So dudes, what’s the deal with Unicode strings?" The
dude part is optional, but apparently the usefulness of Unicode strings is pretty widely appreciated. The Unicode character set
(and useful encodings like UTF-8, UCS-4, ISO 8859-10, etc etc etc) were not mentioned in the first C++ standard. (The 2011
standard added support for string literals with different encodings and some library facilities for converting between encodings,
but the notes below have not been updated to reflect that.)
A couple of comments:
The thought that all one needs to convert between two arbitrary codesets is two types and some kind of state argument is
unfortunate. In particular, encodings may be stateless. The naming of the third parameter as stateT is unfortunate, as what is
really needed is some kind of generalized type that accounts for the issues that abstract encodings will need. The minimum
information that is required includes:
• Identifiers for each of the codesets involved in the conversion. For example, using the iconv family of functions from the Single
Unix Specification (what used to be called X/Open) hosted on the GNU/Linux operating system allows bi-directional mapping
between far more than the following tantalizing possibilities:
(An edited list taken from `iconv --list` on a Red Hat 6.2/Intel system:
8859_1, 8859_9, 10646-1:1993, 10646-1:1993/UCS4, ARABIC, ARABIC7,
ASCII, EUC-CN, EUC-JP, EUC-KR, EUC-TW, GREEK-CCIcode, GREEK, GREEK7-OLD,
GREEK7, GREEK8, HEBREW, ISO-8859-1, ISO-8859-2, ISO-8859-3,
ISO-8859-4, ISO-8859-5, ISO-8859-6, ISO-8859-7, ISO-8859-8,
ISO-8859-9, ISO-8859-10, ISO-8859-11, ISO-8859-13, ISO-8859-14,
ISO-8859-15, ISO-10646, ISO-10646/UCS2, ISO-10646/UCS4,
ISO-10646/UTF-8, ISO-10646/UTF8, SHIFT-JIS, SHIFT_JIS, UCS-2, UCS-4,
UCS2, UCS4, UNICODE, UNICODEBIG, UNICODELIcodeLE, US-ASCII, US, UTF-8,
UTF-16, UTF8, UTF16).

For iconv-based implementations, string literals for each of the encodings (i.e. "UCS-2" and "UTF-8") are necessary, although
for other, non-iconv implementations a table of enumerated values or some other mechanism may be required.
• Maximum length of the identifying string literal.
• Some encodings require explicit endian-ness. As such, some kind of endian marker or other byte-order marker will be necessary. See "Footnotes for C/C++ developers" in Haible for more information on UCS-2/Unicode endian issues. (Summary: big
endian seems most likely, however implementations, most notably Microsoft, vary.)
• Types representing the conversion state, for conversions involving the machinery in the "C" library, or the conversion descriptor,
for conversions using iconv (such as the type iconv_t.) Note that the conversion descriptor encodes more information than a
simple encoding state type.
• Conversion descriptors for both directions of encoding. (i.e., both UCS-2 to UTF-8 and UTF-8 to UCS-2.)
• Something to indicate if the conversion requested if valid.
• Something to represent if the conversion descriptors are valid.
• Some way to enforce strict type checking on the internal and external types. As part of this, the size of the internal and external
types will need to be known.
8.2.2.2.3

Other Issues

In addition, multi-threaded and multi-locale environments also impact the design and requirements for code conversions. In particular, they affect the required specialization codecvt when implemented using standard "C" functions.
Three problems arise, one big, one of medium importance, and one small.

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First, the small: mcsrtombs and wcsrtombs may not be multithread-safe on all systems required by the GNU tools. For
GNU/Linux and glibc, this is not an issue.
Of medium concern, in the grand scope of things, is that the functions used to implement this specialization work on nullterminated strings. Buffers, especially file buffers, may not be null-terminated, thus giving conversions that end prematurely or
are otherwise incorrect. Yikes!
The last, and fundamental problem, is the assumption of a global locale for all the "C" functions referenced above. For something
like C++ iostreams (where codecvt is explicitly used) the notion of multiple locales is fundamental. In practice, most users may
not run into this limitation. However, as a quality of implementation issue, the GNU C++ library would like to offer a solution
that allows multiple locales and or simultaneous usage with computationally correct results. In short, libstdc++ is trying to offer,
as an option, a high-quality implementation, damn the additional complexity!
For the required specialization codecvt, conversions are made between the internal
character set (always UCS4 on GNU/Linux) and whatever the currently selected locale for the LC_CTYPE category implements.
8.2.2.3

Implementation

The two required specializations are implemented as follows:
codecvt
This is a degenerate (i.e., does nothing) specialization. Implementing this was a piece of cake.
codecvt
This specialization, by specifying all the template parameters, pretty much ties the hands of implementors. As such, the implementation is straightforward, involving mcsrtombs for the conversions between char to wchar_t and wcsrtombs for
conversions between wchar_t and char.
Neither of these two required specializations deals with Unicode characters. As such, libstdc++ implements a partial specialization of the codecvt class with an iconv wrapper class, encoding_state as the third template parameter.
This implementation should be standards conformant. First of all, the standard explicitly points out that instantiations on the
third template parameter, stateT, are the proper way to implement non-required conversions. Second of all, the standard says (in
Chapter 17) that partial specializations of required classes are A-OK. Third of all, the requirements for the stateT type elsewhere
in the standard (see 21.1.2 traits typedefs) only indicate that this type be copy constructible.
As such, the type encoding_state is defined as a non-templatized, POD type to be used as the third type of a codecvt instantiation.
This type is just a wrapper class for iconv, and provides an easy interface to iconv functionality.
There are two constructors for encoding_state:
encoding_state() :__in_desc(0), __out_desc(0)
This default constructor sets the internal encoding to some default (currently UCS4) and the external encoding to whatever is
returned by nl_langinfo(CODESET).
encoding_state(const char* __int, const char* __ext)
This constructor takes as parameters string literals that indicate the desired internal and external encoding. There are no defaults
for either argument.
One of the issues with iconv is that the string literals identifying conversions are not standardized. Because of this, the thought
of mandating and/or enforcing some set of pre-determined valid identifiers seems iffy: thus, a more practical (and non-migraine
inducing) strategy was implemented: end-users can specify any string (subject to a pre-determined length qualifier, currently 32
bytes) for encodings. It is up to the user to make sure that these strings are valid on the target system.
void _M_init()
Strangely enough, this member function attempts to open conversion descriptors for a given encoding_state object. If the conversion descriptors are not valid, the conversion descriptors returned will not be valid and the resulting calls to the codecvt
conversion functions will return error.
bool _M_good()

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Provides a way to see if the given encoding_state object has been properly initialized. If the string literals describing the desired
internal and external encoding are not valid, initialization will fail, and this will return false. If the internal and external encodings
are valid, but iconv_open could not allocate conversion descriptors, this will also return false. Otherwise, the object is ready
to convert and will return true.
encoding_state(const encoding_state&)
As iconv allocates memory and sets up conversion descriptors, the copy constructor can only copy the member data pertaining to
the internal and external code conversions, and not the conversion descriptors themselves.
Definitions for all the required codecvt member functions are provided for this specialization, and usage of codecvt is consistent with other codecvt usage.
8.2.2.4

Use

A conversion involving a string literal.
typedef
typedef
typedef
typedef
typedef
typedef

codecvt_base::result
result;
unsigned short
unicode_t;
unicode_t
int_type;
char
ext_type;
encoding_state
state_type;
codecvt unicode_codecvt;

const ext_type*
e_lit = "black pearl jasmine tea";
int
size = strlen(e_lit);
int_type
i_lit_base[24] =
{ 25088, 27648, 24832, 25344, 27392, 8192, 28672, 25856, 24832, 29184,
27648, 8192, 27136, 24832, 29440, 27904, 26880, 28160, 25856, 8192, 29696,
25856, 24832, 2560
};
const int_type*
i_lit = i_lit_base;
const ext_type*
efrom_next;
const int_type*
ifrom_next;
ext_type*
e_arr = new ext_type[size + 1];
ext_type*
eto_next;
int_type*
i_arr = new int_type[size + 1];
int_type*
ito_next;
// construct a locale object with the specialized facet.
locale
loc(locale::classic(), new unicode_codecvt);
// sanity check the constructed locale has the specialized facet.
VERIFY( has_facet(loc) );
const unicode_codecvt& cvt = use_facet(loc);
// convert between const char* and unicode strings
unicode_codecvt::state_type state01("UNICODE", "ISO_8859-1");
initialize_state(state01);
result r1 = cvt.in(state01, e_lit, e_lit + size, efrom_next,
i_arr, i_arr + size, ito_next);
VERIFY( r1 == codecvt_base::ok );
VERIFY( !int_traits::compare(i_arr, i_lit, size) );
VERIFY( efrom_next == e_lit + size );
VERIFY( ito_next == i_arr + size );

8.2.2.5

Future

• a. things that are sketchy, or remain unimplemented: do_encoding, max_length and length member functions are only weakly
implemented. I have no idea how to do this correctly, and in a generic manner. Nathan?
• b. conversions involving std::string

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– how should operators != and == work for string of different/same encoding?
– what is equal? A byte by byte comparison or an encoding then byte comparison?
– conversions between narrow, wide, and unicode strings
• c. conversions involving std::filebuf and std::ostream
– how to initialize the state object in a standards-conformant manner?
– how to synchronize the "C" and "C++" conversion information?
– wchar_t/char internal buffers and conversions between internal/external buffers?
8.2.2.6

Bibliography

[33] Roland McGrathUlrich Drepper, Copyright © 2007 FSF, Chapters 6 Character Set Handling and 7 Locales and
Internationalization .
[34] Ulrich Drepper, Copyright © 2002 .
[35] , Copyright © 1998 ISO.
[36] , Copyright © 1999 ISO.
[37] System Interface Definitions, Issue 7 (IEEE Std. 1003.1-2008) , Copyright © 2008 The Open Group/The
Institute of Electrical and Electronics Engineers, Inc. .
[38] Bjarne Stroustrup, Copyright © 2000 Addison Wesley, Inc., Appendix D, Addison Wesley .
[39] Angelika LangerKlaus Kreft, Advanced Programmer’s Guide and Reference , Copyright © 2000 Addison Wesley Longman, Inc., Addison Wesley Longman .
[40] Clive Feather, A brief description of Normative Addendum 1 , Extended Character Sets.
[41] Bruno Haible, The Unicode HOWTO
[42] Markus Khun, UTF-8 and Unicode FAQ for Unix/Linux

8.2.3

messages

The std::messages facet implements message retrieval functionality equivalent to Java’s java.text.MessageFormat
using either GNU gettext or IEEE 1003.1-200 functions.
8.2.3.1

Requirements

The std::messages facet is probably the most vaguely defined facet in the standard library. It’s assumed that this facility
was built into the standard library in order to convert string literals from one locale to the other. For instance, converting the "C"
locale’s const char* c ="please" to a German-localized "bitte" during program execution.
22.2.7.1 - Template class messages [lib.locale.messages]
This class has three public member functions, which directly correspond to three protected virtual member functions.
The public member functions are:
catalog open(const string&, const locale&) const
string_type get(catalog, int, int, const string_type&) const
void close(catalog) const
While the virtual functions are:
catalog do_open(const string& name, const locale& loc) const

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-1- Returns: A value that may be passed to get() to retrieve a message, from the message catalog identified
by the string name according to an implementation-defined mapping. The result can be used until it is passed to
close(). Returns a value less than 0 if no such catalog can be opened.
string_type do_get(catalog cat, int set , int msgid, const string_type& dfault) const
-3- Requires: A catalog cat obtained from open() and not yet closed. -4- Returns: A message identified by
arguments set, msgid, and dfault, according to an implementation-defined mapping. If no such message can
be found, returns dfault.
void do_close(catalog cat) const
-5- Requires: A catalog cat obtained from open() and not yet closed. -6- Effects: Releases unspecified resources
associated with cat. -7- Notes: The limit on such resources, if any, is implementation-defined.
8.2.3.2

Design

A couple of notes on the standard.
First, why is messages_base::catalog specified as a typedef to int? This makes sense for implementations that use
catopen and define nl_catd as int, but not for others. Fortunately, it’s not heavily used and so only a minor irritant. This has
been reported as a possible defect in the standard (LWG 2028).
Second, by making the member functions const, it is impossible to save state in them. Thus, storing away information used in
the ’open’ member function for use in ’get’ is impossible. This is unfortunate.
The ’open’ member function in particular seems to be oddly designed. The signature seems quite peculiar. Why specify a const
string& argument, for instance, instead of just const char*? Or, why specify a const locale& argument that is to
be used in the ’get’ member function? How, exactly, is this locale argument useful? What was the intent? It might make sense if
a locale argument was associated with a given default message string in the ’open’ member function, for instance. Quite murky
and unclear, on reflection.
Lastly, it seems odd that messages, which explicitly require code conversion, don’t use the codecvt facet. Because the messages
facet has only one template parameter, it is assumed that ctype, and not codecvt, is to be used to convert between character sets.
It is implicitly assumed that the locale for the default message string in ’get’ is in the "C" locale. Thus, all source code is assumed
to be written in English, so translations are always from "en_US" to other, explicitly named locales.
8.2.3.3

Implementation

8.2.3.3.1

Models

This is a relatively simple class, on the face of it. The standard specifies very little in concrete terms, so generic implementations
that are conforming yet do very little are the norm. Adding functionality that would be useful to programmers and comparable
to Java’s java.text.MessageFormat takes a bit of work, and is highly dependent on the capabilities of the underlying operating
system.
Three different mechanisms have been provided, selectable via configure flags:
• generic
This model does very little, and is what is used by default.
• gnu
The gnu model is complete and fully tested. It’s based on the GNU gettext package, which is part of glibc. It uses the functions
textdomain, bindtextdomain, gettext to implement full functionality. Creating message catalogs is a relatively
straight-forward process and is lightly documented below, and fully documented in gettext’s distributed documentation.

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• ieee_1003.1-200x
This is a complete, though untested, implementation based on the IEEE standard. The functions catopen, catgets,
catclose are used to retrieve locale-specific messages given the appropriate message catalogs that have been constructed
for their use. Note, the script po2msg.sed that is part of the gettext distribution can convert gettext catalogs into catalogs
that catopen can use.
A new, standards-conformant non-virtual member function signature was added for ’open’ so that a directory could be specified
with a given message catalog. This simplifies calling conventions for the gnu model.
8.2.3.3.2

The GNU Model

The messages facet, because it is retrieving and converting between characters sets, depends on the ctype and perhaps the codecvt
facet in a given locale. In addition, underlying "C" library locale support is necessary for more than just the LC_MESSAGES
mask: LC_CTYPE is also necessary. To avoid any unpleasantness, all bits of the "C" mask (i.e. LC_ALL) are set before retrieving
messages.
Making the message catalogs can be initially tricky, but become quite simple with practice. For complete info, see the gettext
documentation. Here’s an idea of what is required:
• Make a source file with the required string literals that need to be translated. See intl/string_literals.cc for an
example.
• Make initial catalog (see "4 Making the PO Template File" from the gettext docs).
xgettext --c++ --debug string_literals.cc -o libstdc++.pot
• Make language and country-specific locale catalogs.
cp libstdc++.pot fr_FR.po
cp libstdc++.pot de_DE.po
• Edit localized catalogs in emacs so that strings are translated.
emacs fr_FR.po
• Make the binary mo files.
msgfmt fr_FR.po -o fr_FR.mo
msgfmt de_DE.po -o de_DE.mo
• Copy the binary files into the correct directory structure.
cp fr_FR.mo (dir)/fr_FR/LC_MESSAGES/libstdc++.mo
cp de_DE.mo (dir)/de_DE/LC_MESSAGES/libstdc++.mo
• Use the new message catalogs.
locale loc_de("de_DE");
use_facet >(loc_de).open("libstdc++", locale(), dir);
8.2.3.4

Use

A simple example using the GNU model of message conversion.
#include 
#include 
using namespace std;
void test01()
{
typedef messages::catalog catalog;

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const char* dir =
"/mnt/egcs/build/i686-pc-linux-gnu/libstdc++/po/share/locale";
const locale loc_de("de_DE");
const messages& mssg_de = use_facet >(loc_de);
catalog cat_de = mssg_de.open("libstdc++", loc_de, dir);
string s01 = mssg_de.get(cat_de, 0, 0, "please");
string s02 = mssg_de.get(cat_de, 0, 0, "thank you");
cout << "please in german:" << s01 << ’\n’;
cout << "thank you in german:" << s02 << ’\n’;
mssg_de.close(cat_de);
}

8.2.3.5

Future

• Things that are sketchy, or remain unimplemented:
– _M_convert_from_char, _M_convert_to_char are in flux, depending on how the library ends up doing character set conversions. It might not be possible to do a real character set based conversion, due to the fact that the template parameter for
messages is not enough to instantiate the codecvt facet (1 supplied, need at least 2 but would prefer 3).
– There are issues with gettext needing the global locale set to extract a message. This dependence on the global locale makes
the current "gnu" model non MT-safe. Future versions of glibc, i.e. glibc 2.3.x will fix this, and the C++ library bits are
already in place.
• Development versions of the GNU "C" library, glibc 2.3 will allow a more efficient, MT implementation of std::messages, and
will allow the removal of the _M_name_messages data member. If this is done, it will change the library ABI. The C++ parts
to support glibc 2.3 have already been coded, but are not in use: once this version of the "C" library is released, the marked
parts of the messages implementation can be switched over to the new "C" library functionality.
• At some point in the near future, std::numpunct will probably use std::messages facilities to implement truename/falsename
correctly. This is currently not done, but entries in libstdc++.pot have already been made for "true" and "false" string literals,
so all that remains is the std::numpunct coding and the configure/make hassles to make the installed library search its own
catalog. Currently the libstdc++.mo catalog is only searched for the testsuite cases involving messages members.
• The following member functions:
catalog open(const basic_string& __s, const locale& __loc) const
catalog open(const basic_string&, const locale&, const char*) const;
Don’t actually return a "value less than 0 if no such catalog can be opened" as required by the standard in the "gnu" model. As
of this writing, it is unknown how to query to see if a specified message catalog exists using the gettext package.
8.2.3.6

Bibliography

[43] Roland McGrathUlrich Drepper, Copyright © 2007 FSF, Chapters 6 Character Set Handling, and 7 Locales and
Internationalization .
[44] Ulrich Drepper, Copyright © 2002 .
[45] , Copyright © 1998 ISO.
[46] , Copyright © 1999 ISO.
[47] System Interface Definitions, Issue 7 (IEEE Std. 1003.1-2008) , Copyright © 2008 The Open Group/The
Institute of Electrical and Electronics Engineers, Inc. .
[48] Bjarne Stroustrup, Copyright © 2000 Addison Wesley, Inc., Appendix D, Addison Wesley .
[49] Angelika LangerKlaus Kreft, Advanced Programmer’s Guide and Reference , Copyright © 2000 Addison Wesley Longman, Inc., Addison Wesley Longman .

The GNU C++ Library Manual

[50]

API Specifications, Java Platform
java.util.ResourceBundle .

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, java.util.Properties, java.text.MessageFormat, java.util.Locale,

[51] GNU gettext tools, version 0.10.38, Native Language Support Library and Tools.

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Chapter 9

Containers
9.1

Sequences

9.1.1

list

9.1.1.1

list::size() is O(n)

Yes it is, at least using the Dual ABI, and that’s okay. This is a decision that we preserved when we imported SGI’s STL
implementation. The following is quoted from their FAQ:
The size() member function, for list and slist, takes time proportional to the number of elements in the list. This
was a deliberate tradeoff. The only way to get a constant-time size() for linked lists would be to maintain an extra
member variable containing the list’s size. This would require taking extra time to update that variable (it would
make splice() a linear time operation, for example), and it would also make the list larger. Many list algorithms don’t
require that extra word (algorithms that do require it might do better with vectors than with lists), and, when it is
necessary to maintain an explicit size count, it’s something that users can do themselves.
This choice is permitted by the C++ standard. The standard says that size() “should” be constant time, and “should”
does not mean the same thing as “shall”. This is the officially recommended ISO wording for saying that an implementation is supposed to do something unless there is a good reason not to.
One implication of linear time size(): you should never write
if (L.size() == 0)
...

Instead, you should write
if (L.empty())
...

9.2
9.2.1

Associative
Insertion Hints

Section [23.1.2], Table 69, of the C++ standard lists this function for all of the associative containers (map, set, etc):
a.insert(p,t);

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where ’p’ is an iterator into the container ’a’, and ’t’ is the item to insert. The standard says that “t is inserted as close as possible
to the position just prior to p.” (Library DR #233 addresses this topic, referring to N1780. Since version 4.2 GCC implements
the resolution to DR 233, so that insertions happen as close as possible to the hint. For earlier releases the hint was only used as
described below.
Here we’ll describe how the hinting works in the libstdc++ implementation, and what you need to do in order to take advantage
of it. (Insertions can change from logarithmic complexity to amortized constant time, if the hint is properly used.) Also, since
the current implementation is based on the SGI STL one, these points may hold true for other library implementations also, since
the HP/SGI code is used in a lot of places.
In the following text, the phrases greater than and less than refer to the results of the strict weak ordering imposed on the
container by its comparison object, which defaults to (basically) “<”. Using those phrases is semantically sloppy, but I didn’t
want to get bogged down in syntax. I assume that if you are intelligent enough to use your own comparison objects, you are also
intelligent enough to assign “greater” and “lesser” their new meanings in the next paragraph. *grin*
If the hint parameter (’p’ above) is equivalent to:
• begin(), then the item being inserted should have a key less than all the other keys in the container. The item will be inserted
at the beginning of the container, becoming the new entry at begin().
• end(), then the item being inserted should have a key greater than all the other keys in the container. The item will be inserted
at the end of the container, becoming the new entry before end().
• neither begin() nor end(), then: Let h be the entry in the container pointed to by hint, that is, h =*hint. Then the
item being inserted should have a key less than that of h, and greater than that of the item preceding h. The new item will be
inserted between h and h’s predecessor.
For multimap and multiset, the restrictions are slightly looser: “greater than” should be replaced by “not less than”and
“less than” should be replaced by “not greater than.” (Why not replace greater with greater-than-or-equal-to? You probably could
in your head, but the mathematicians will tell you that it isn’t the same thing.)
If the conditions are not met, then the hint is not used, and the insertion proceeds as if you had called a.insert(t) instead.
(Note that GCC releases prior to 3.0.2 had a bug in the case with hint ==begin() for the map and set classes. You should
not use a hint argument in those releases.)
This behavior goes well with other containers’ insert() functions which take an iterator: if used, the new item will be inserted
before the iterator passed as an argument, same as the other containers.
Note also that the hint in this implementation is a one-shot. The older insertion-with-hint routines check the immediately
surrounding entries to ensure that the new item would in fact belong there. If the hint does not point to the correct place, then no
further local searching is done; the search begins from scratch in logarithmic time.

9.2.2

bitset

9.2.2.1

Size Variable

No, you cannot write code of the form
#include 
void foo (size_t n)
{
std::bitset
bits;
....
}

because n must be known at compile time. Your compiler is correct; it is not a bug. That’s the way templates work. (Yes, it is a
feature.)
There are a couple of ways to handle this kind of thing. Please consider all of them before passing judgement. They include, in
no particular order:

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• A very large N in bitset.
• A container.
• Extremely weird solutions.
A very large N in bitset. It has been pointed out a few times in newsgroups that N bits only takes up (N/8) bytes on most
systems, and division by a factor of eight is pretty impressive when speaking of memory. Half a megabyte given over to a bitset
(recall that there is zero space overhead for housekeeping info; it is known at compile time exactly how large the set is) will hold
over four million bits. If you’re using those bits as status flags (e.g., “changed”/“unchanged” flags), that’s a lot of state.
You can then keep track of the “maximum bit used” during some testing runs on representative data, make note of how many of
those bits really need to be there, and then reduce N to a smaller number. Leave some extra space, of course. (If you plan to write
code like the incorrect example above, where the bitset is a local variable, then you may have to talk your compiler into allowing
that much stack space; there may be zero space overhead, but it’s all allocated inside the object.)
A container. The Committee made provision for the space savings possible with that (N/8) usage previously mentioned,
so that you don’t have to do wasteful things like Container or Container. Specifically, vector
 is required to be specialized for that space savings.
The problem is that vector doesn’t behave like a normal vector anymore. There have been journal articles which
discuss the problems (the ones by Herb Sutter in the May and July/August 1999 issues of C++ Report cover it well). Future
revisions of the ISO C++ Standard will change the requirement for vector specialization. In the meantime, deque<
bool> is recommended (although its behavior is sane, you probably will not get the space savings, but the allocation scheme is
different than that of vector).
Extremely weird solutions. If you have access to the compiler and linker at runtime, you can do something insane, like figuring
out just how many bits you need, then writing a temporary source code file. That file contains an instantiation of bitset for the
required number of bits, inside some wrapper functions with unchanging signatures. Have your program then call the compiler
on that file using Position Independent Code, then open the newly-created object file and load those wrapper functions. You’ll
have an instantiation of bitset for the exact N that you need at the time. Don’t forget to delete the temporary files. (Yes,
this can be, and has been, done.)
This would be the approach of either a visionary genius or a raving lunatic, depending on your programming and management
style. Probably the latter.
Which of the above techniques you use, if any, are up to you and your intended application. Some time/space profiling is indicated
if it really matters (don’t just guess). And, if you manage to do anything along the lines of the third category, the author would
love to hear from you...
Also note that the implementation of bitset used in libstdc++ has some extensions.
9.2.2.2

Type String

Bitmasks do not take char* nor const char* arguments in their constructors. This is something of an accident, but you can read
about the problem: follow the library’s “Links” from the homepage, and from the C++ information “defect reflector” link, select
the library issues list. Issue number 116 describes the problem.
For now you can simply make a temporary string object using the constructor expression:
std::bitset<5> b ( std::string("10110") );

instead of
std::bitset<5> b ( "10110" );

// invalid

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Unordered Associative
Insertion Hints

Here is how the hinting works in the libstdc++ implementation of unordered containers, and the rationale behind this behavior.
In the following text, the phrase equivalent to refer to the result of the invocation of the equal predicate imposed on the container
by its key_equal object, which defaults to (basically) “==”.
Unordered containers can be seen as a std::vector of std::forward_list. The std::vector represents the buckets
and each std::forward_list is the list of nodes belonging to the same bucket. When inserting an element in such a data
structure we first need to compute the element hash code to find the bucket to insert the element to, the second step depends on
the uniqueness of elements in the container.
In the case of std::unordered_set and std::unordered_map you need to look through all bucket’s elements for an
equivalent one. If there is none the insertion can be achieved, otherwise the insertion fails. As we always need to loop though all
bucket’s elements, the hint doesn’t tell us if the element is already present, and we don’t have any constraint on where the new
element is to be inserted, the hint won’t be of any help and will then be ignored.
In the case of std::unordered_multiset and std::unordered_multimap equivalent elements must be linked together so that the equal_range(const key_type&) can return the range of iterators pointing to all equivalent elements.
This is where hinting can be used to point to another equivalent element already part of the container and so skip all non equivalent elements of the bucket. So to be useful the hint shall point to an element equivalent to the one being inserted. The new
element will be then inserted right after the hint. Note that because of an implementation detail inserting after a node can require
updating the bucket of the following node. To check if the next bucket is to be modified we need to compute the following node’s
hash code. So if you want your hint to be really efficient it should be followed by another equivalent element, the implementation
will detect this equivalence and won’t compute next element hash code.
It is highly advised to start using unordered containers hints only if you have a benchmark that will demonstrate the benefit of it.
If you don’t then do not use hints, it might do more harm than good.

9.3.2

Hash Code

9.3.2.1

Hash Code Caching Policy

The unordered containers in libstdc++ may cache the hash code for each element alongside the element itself. In some cases not
recalculating the hash code every time it’s needed can improve performance, but the additional memory overhead can also reduce
performance, so whether an unordered associative container caches the hash code or not depends on the properties described
below.
The C++ standard requires that erase and swap operations must not throw exceptions. Those operations might need an
element’s hash code, but cannot use the hash function if it could throw. This means the hash codes will be cached unless the hash
function has a non-throwing exception specification such as noexcept or throw().
If the hash function is non-throwing then libstdc++ doesn’t need to cache the hash code for correctness, but might still do so
for performance if computing a hash code is an expensive operation, as it may be for arbitrarily long strings. As an extension
libstdc++ provides a trait type to describe whether a hash function is fast. By default hash functions are assumed to be fast unless
the trait is specialized for the hash function and the trait’s value is false, in which case the hash code will always be cached. The
trait can be specialized for user-defined hash functions like so:
#include 
struct hasher
{
std::size_t operator()(int val) const noexcept
{
// Some very slow computation of a hash code from an int !
...
}
}

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namespace std
{
template<>
struct __is_fast_hash : std::false_type
{ };
}

9.4
9.4.1

Interacting with C
Containers vs. Arrays

You’re writing some code and can’t decide whether to use builtin arrays or some kind of container. There are compelling reasons
to use one of the container classes, but you’re afraid that you’ll eventually run into difficulties, change everything back to arrays,
and then have to change all the code that uses those data types to keep up with the change.
If your code makes use of the standard algorithms, this isn’t as scary as it sounds. The algorithms don’t know, nor care, about the
kind of “container” on which they work, since the algorithms are only given endpoints to work with. For the container classes,
these are iterators (usually begin() and end(), but not always). For builtin arrays, these are the address of the first element
and the past-the-end element.
Some very simple wrapper functions can hide all of that from the rest of the code. For example, a pair of functions called
beginof can be written, one that takes an array, another that takes a vector. The first returns a pointer to the first element, and
the second returns the vector’s begin() iterator.
The functions should be made template functions, and should also be declared inline. As pointed out in the comments in the code
below, this can lead to beginof being optimized out of existence, so you pay absolutely nothing in terms of increased code size
or execution time.
The result is that if all your algorithm calls look like
std::transform(beginof(foo), endof(foo), beginof(foo), SomeFunction);

then the type of foo can change from an array of ints to a vector of ints to a deque of ints and back again, without ever changing
any client code.
// beginof
template
inline typename vector::iterator
beginof(vector &v)
{ return v.begin(); }
template
inline T*
beginof(T (&array)[sz]) { return array; }
// endof
template
inline typename vector::iterator
endof(vector &v)
{ return v.end(); }
template
inline T*
endof(T (&array)[sz]) { return array + sz; }
// lengthof
template
inline typename vector::size_type
lengthof(vector &v)

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{ return v.size(); }
template
inline unsigned int
lengthof(T (&)[sz]) { return sz; }

Astute readers will notice two things at once: first, that the container class is still a vector instead of a more general
Container. This would mean that three functions for deque would have to be added, another three for list, and so
on. This is due to problems with getting template resolution correct; I find it easier just to give the extra three lines and avoid
confusion.
Second, the line
inline unsigned int lengthof (T (&)[sz]) { return sz; }

looks just weird! Hint: unused parameters can be left nameless.

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Chapter 10

Iterators
10.1

Predefined

10.1.1

Iterators vs. Pointers

The following FAQ entry points out that iterators are not implemented as pointers. They are a generalization of pointers, but they
are implemented in libstdc++ as separate classes.
Keeping that simple fact in mind as you design your code will prevent a whole lot of difficult-to-understand bugs.
You can think of it the other way ’round, even. Since iterators are a generalization, that means that pointers are iterators, and that
pointers can be used whenever an iterator would be. All those functions in the Algorithms section of the Standard will work just
as well on plain arrays and their pointers.
That doesn’t mean that when you pass in a pointer, it gets wrapped into some special delegating iterator-to-pointer class with a
layer of overhead. (If you think that’s the case anywhere, you don’t understand templates to begin with...) Oh, no; if you pass
in a pointer, then the compiler will instantiate that template using T* as a type, and good old high-speed pointer arithmetic as its
operations, so the resulting code will be doing exactly the same things as it would be doing if you had hand-coded it yourself (for
the 273rd time).
How much overhead is there when using an iterator class? Very little. Most of the layering classes contain nothing but typedefs,
and typedefs are "meta-information" that simply tell the compiler some nicknames; they don’t create code. That information gets
passed down through inheritance, so while the compiler has to do work looking up all the names, your runtime code does not.
(This has been a prime concern from the beginning.)

10.1.2

One Past the End

This starts off sounding complicated, but is actually very easy, especially towards the end. Trust me.
Beginners usually have a little trouble understand the whole ’past-the-end’ thing, until they remember their early algebra classes
(see, they told you that stuff would come in handy!) and the concept of half-open ranges.
First, some history, and a reminder of some of the funkier rules in C and C++ for builtin arrays. The following rules have always
been true for both languages:
1. You can point anywhere in the array, or to the first element past the end of the array. A pointer that points to one past the
end of the array is guaranteed to be as unique as a pointer to somewhere inside the array, so that you can compare such
pointers safely.
2. You can only dereference a pointer that points into an array. If your array pointer points outside the array -- even to just
one past the end -- and you dereference it, Bad Things happen.

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3. Strictly speaking, simply pointing anywhere else invokes undefined behavior. Most programs won’t puke until such a
pointer is actually dereferenced, but the standards leave that up to the platform.
The reason this past-the-end addressing was allowed is to make it easy to write a loop to go over an entire array, e.g., while (*d++
= *s++);.
So, when you think of two pointers delimiting an array, don’t think of them as indexing 0 through n-1. Think of them as boundary
markers:
beginning
end
|
|
|
|
|
|
|
|
V
V
array of N elements
|---|---|--...--|---|---|
| 0 | 1 | ... |N-2|N-1|
|---|---|--...--|---|---|
^
|
|
|
|
beginning

^
|
|
|
|
end

This is bad. Always having to
remember to add or subtract one.
Off-by-one bugs very common here.

This is good. This is safe. This
is guaranteed to work. Just don’t
dereference ’end’.

See? Everything between the boundary markers is chapter of the array. Simple.
Now think back to your junior-high school algebra course, when you were learning how to draw graphs. Remember that a
graph terminating with a solid dot meant, "Everything up through this point," and a graph terminating with an open dot meant,
"Everything up to, but not including, this point," respectively called closed and open ranges? Remember how closed ranges were
written with brackets, [a,b], and open ranges were written with parentheses, (a,b)?
The boundary markers for arrays describe a half-open range, starting with (and including) the first element, and ending with (but
not including) the last element: [beginning,end). See, I told you it would be simple in the end.
Iterators, and everything working with iterators, follows this same time-honored tradition. A container’s begin() method
returns an iterator referring to the first element, and its end() method returns a past-the-end iterator, which is guaranteed to be
unique and comparable against any other iterator pointing into the middle of the container.
Container constructors, container methods, and algorithms, all take pairs of iterators describing a range of values on which to
operate. All of these ranges are half-open ranges, so you pass the beginning iterator as the starting parameter, and the one-pastthe-end iterator as the finishing parameter.
This generalizes very well. You can operate on sub-ranges quite easily this way; functions accepting a [first,last) range don’t
know or care whether they are the boundaries of an entire {array, sequence, container, whatever}, or whether they only enclose
a few elements from the center. This approach also makes zero-length sequences very simple to recognize: if the two endpoints
compare equal, then the {array, sequence, container, whatever} is empty.
Just don’t dereference end().

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Chapter 11

Algorithms
The neatest accomplishment of the algorithms section is that all the work is done via iterators, not containers directly. This means
two important things:
1. Anything that behaves like an iterator can be used in one of these algorithms. Raw pointers make great candidates, thus
built-in arrays are fine containers, as well as your own iterators.
2. The algorithms do not (and cannot) affect the container as a whole; only the things between the two iterator endpoints. If
you pass a range of iterators only enclosing the middle third of a container, then anything outside that range is inviolate.
Even strings can be fed through the algorithms here, although the string class has specialized versions of many of these functions
(for example, string::find()). Most of the examples on this page will use simple arrays of integers as a playground for
algorithms, just to keep things simple. The use of N as a size in the examples is to keep things easy to read but probably won’t
be valid code. You can use wrappers such as those described in the containers section to keep real code readable.
The single thing that trips people up the most is the definition of range used with iterators; the famous "past-the-end" rule that
everybody loves to hate. The iterators section of this document has a complete explanation of this simple rule that seems to cause
so much confusion. Once you get range into your head (it’s not that hard, honest!), then the algorithms are a cakewalk.

11.1

Mutating

11.1.1 swap
11.1.1.1

Specializations

If you call std::swap(x,y); where x and y are standard containers, then the call will automatically be replaced by a call
to x.swap(y); instead.
This allows member functions of each container class to take over, and containers’ swap functions should have O(1) complexity
according to the standard. (And while "should" allows implementations to behave otherwise and remain compliant, this implementation does in fact use constant-time swaps.) This should not be surprising, since for two containers of the same type to swap
contents, only some internal pointers to storage need to be exchanged.

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Chapter 12

Numerics
12.1

Complex

12.1.1

complex Processing

Using complex<> becomes even more comple- er, sorry, complicated, with the not-quite-gratuitously-incompatible addition of
complex types to the C language. David Tribble has compiled a list of C++98 and C99 conflict points; his description of C’s new
type versus those of C++ and how to get them playing together nicely is here.
complex<> is intended to be instantiated with a floating-point type. As long as you meet that and some other basic requirements,
then the resulting instantiation has all of the usual math operators defined, as well as definitions of op<< and op>> that work
with iostreams: op<< prints (u,v) and op>> can read u, (u), and (u,v).
As an extension to C++11 and for increased compatibility with C,  includes both  and the C99
 (if the C library provides it).

12.2

Generalized Operations

There are four generalized functions in the  header that follow the same conventions as those in . Each
of them is overloaded: one signature for common default operations, and a second for fully general operations. Their names are
self-explanatory to anyone who works with numerics on a regular basis:
• accumulate
• inner_product
• partial_sum
• adjacent_difference
Here is a simple example of the two forms of accumulate.
int
int

ar[50];
someval = somefunction();

// ...initialize members of ar to something...
int
int
int

sum
= std::accumulate(ar,ar+50,0);
sum_stuff = std::accumulate(ar,ar+50,someval);
product
= std::accumulate(ar,ar+50,1,std::multiplies());

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The first call adds all the members of the array, using zero as an initial value for sum. The second does the same, but uses
someval as the starting value (thus, sum_stuff ==sum + someval). The final call uses the second of the two signatures,
and multiplies all the members of the array; here we must obviously use 1 as a starting value instead of 0.
The other three functions have similar dual-signature forms.

12.3

Interacting with C

12.3.1

Numerics vs. Arrays

One of the major reasons why FORTRAN can chew through numbers so well is that it is defined to be free of pointer aliasing, an
assumption that C89 is not allowed to make, and neither is C++98. C99 adds a new keyword, restrict, to apply to individual
pointers. The C++ solution is contained in the library rather than the language (although many vendors can be expected to add
this to their compilers as an extension).
That library solution is a set of two classes, five template classes, and "a whole bunch" of functions. The classes are required to
be free of pointer aliasing, so compilers can optimize the daylights out of them the same way that they have been for FORTRAN.
They are collectively called valarray, although strictly speaking this is only one of the five template classes, and they are
designed to be familiar to people who have worked with the BLAS libraries before.

12.3.2

C99

In addition to the other topics on this page, we’ll note here some of the C99 features that appear in libstdc++.
The C99 features depend on the --enable-c99 configure flag. This flag is already on by default, but it can be disabled by the
user. Also, the configuration machinery will disable it if the necessary support for C99 (e.g., header files) cannot be found.
As of GCC 3.0, C99 support includes classification functions such as isnormal, isgreater, isnan, etc. The functions
used for ’long long’ support such as strtoll are supported, as is the lldiv_t typedef. Also supported are the wide character
functions using ’long long’, like wcstoll.

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Chapter 13

Input and Output
13.1

Iostream Objects

To minimize the time you have to wait on the compiler, it’s good to only include the headers you really need. Many people
simply include  when they don’t need to -- and that can penalize your runtime as well. Here are some tips on
which header to use for which situations, starting with the simplest.
 should be included whenever you simply need the name of an I/O-related class, such as "ofstream" or "basic_
streambuf". Like the name implies, these are forward declarations. (A word to all you fellow old school programmers: trying
to forward declare classes like "class istream;" won’t work. Look in the  header if you’d like to know why.)
For example,
#include 
class MyClass
{
....
std::ifstream&
};

input_file;

extern std::ostream& operator<< (std::ostream&, MyClass&);

 declares the base classes for the entire I/O stream hierarchy, std::ios_base and std::basic_ios, the
counting types std::streamoff and std::streamsize, the file positioning type std::fpos, and the various manipulators like std::
hex, std::fixed, std::noshowbase, and so forth.
The ios_base class is what holds the format flags, the state flags, and the functions which change them (setf(), width(),
precision(), etc). You can also store extra data and register callback functions through ios_base, but that has been
historically underused. Anything which doesn’t depend on the type of characters stored is consolidated here.
The class template basic_ios is the highest class template in the hierarchy; it is the first one depending on the character type,
and holds all general state associated with that type: the pointer to the polymorphic stream buffer, the facet information, etc.
 declares the class template basic_streambuf, and two standard instantiations, streambuf and wstreambuf.
If you need to work with the vastly useful and capable stream buffer classes, e.g., to create a new form of storage transport, this
header is the one to include.
 and  are the headers to include when you are using the overloaded >> and << operators, or any of
the other abstract stream formatting functions. For example,
#include 
std::ostream& operator<< (std::ostream& os, MyClass& c)
{
return os << c.data1() << c.data2();
}

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The std::istream and std::ostream classes are the abstract parents of the various concrete implementations. If you are only using
the interfaces, then you only need to use the appropriate interface header.
 provides "extractors and inserters that alter information maintained by class ios_base and its derived classes,"
such as std::setprecision and std::setw. If you need to write expressions like os << setw(3); or is >>
setbase(8);, you must include .
 and  declare the six stringstream and fstream classes. As they are the standard concrete descendants
of istream and ostream, you will already know about them.
Finally,  provides the eight standard global objects (cin, cout, etc). To do this correctly, this header also
provides the contents of the  and  headers, but nothing else. The contents of this header look like:
#include 
#include 
namespace std
{
extern istream cin;
extern ostream cout;
....
// this is explained below
static ios_base::Init __foo;
}

// not its real name

Now, the runtime penalty mentioned previously: the global objects must be initialized before any of your own code uses them;
this is guaranteed by the standard. Like any other global object, they must be initialized once and only once. This is typically
done with a construct like the one above, and the nested class ios_base::Init is specified in the standard for just this reason.
How does it work? Because the header is included before any of your code, the __foo object is constructed before any of your
objects. (Global objects are built in the order in which they are declared, and destroyed in reverse order.) The first time the
constructor runs, the eight stream objects are set up.
The static keyword means that each object file compiled from a source file containing  will have its own private
copy of __foo. There is no specified order of construction across object files (it’s one of those pesky NP complete problems that
make life so interesting), so one copy in each object file means that the stream objects are guaranteed to be set up before any of
your code which uses them could run, thereby meeting the requirements of the standard.
The penalty, of course, is that after the first copy of __foo is constructed, all the others are just wasted processor time. The time
spent is merely for an increment-and-test inside a function call, but over several dozen or hundreds of object files, that time can
add up. (It’s not in a tight loop, either.)
The lesson? Only include  when you need to use one of the standard objects in that source file; you’ll pay less
startup time. Only include the header files you need to in general; your compile times will go down when there’s less parsing
work to do.

13.2

Stream Buffers

13.2.1

Derived streambuf Classes

Creating your own stream buffers for I/O can be remarkably easy. If you are interested in doing so, we highly recommend two
very excellent books: Standard C++ IOStreams and Locales by Langer and Kreft, ISBN 0-201-18395-1, and The C++ Standard
Library by Nicolai Josuttis, ISBN 0-201-37926-0. Both are published by Addison-Wesley, who isn’t paying us a cent for saying
that, honest.
Here is a simple example, io/outbuf1, from the Josuttis text. It transforms everything sent through it to uppercase. This version
assumes many things about the nature of the character type being used (for more information, read the books or the newsgroups):
#include 
#include 

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#include 
#include 
class outbuf : public std::streambuf
{
protected:
/* central output function
* - print characters in uppercase mode
*/
virtual int_type overflow (int_type c) {
if (c != EOF) {
// convert lowercase to uppercase
c = std::toupper(static_cast(c),getloc());
// and write the character to the standard output
if (putchar(c) == EOF) {
return EOF;
}
}
return c;
}
};
int main()
{
// create special output buffer
outbuf ob;
// initialize output stream with that output buffer
std::ostream out(&ob);
out << "31 hexadecimal: "
<< std::hex << 31 << std::endl;
return 0;
}

Try it yourself! More examples can be found in 3.1.x code, in include/ext/*_filebuf.h, and in the article Filtering
Streambufs by James Kanze.

13.2.2

Buffering

First, are you sure that you understand buffering? Particularly the fact that C++ may not, in fact, have anything to do with it?
The rules for buffering can be a little odd, but they aren’t any different from those of C. (Maybe that’s why they can be a bit odd.)
Many people think that writing a newline to an output stream automatically flushes the output buffer. This is true only when the
output stream is, in fact, a terminal and not a file or some other device -- and that may not even be true since C++ says nothing
about files nor terminals. All of that is system-dependent. (The "newline-buffer-flushing only occurring on terminals" thing is
mostly true on Unix systems, though.)
Some people also believe that sending endl down an output stream only writes a newline. This is incorrect; after a newline
is written, the buffer is also flushed. Perhaps this is the effect you want when writing to a screen -- get the text out as soon as
possible, etc -- but the buffering is largely wasted when doing this to a file:
output << "a line of text" << endl;
output << some_data_variable << endl;
output << "another line of text" << endl;

The proper thing to do in this case to just write the data out and let the libraries and the system worry about the buffering. If you
need a newline, just write a newline:
output << "a line of text\n"
<< some_data_variable << ’\n’

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<< "another line of text\n";

I have also joined the output statements into a single statement. You could make the code prettier by moving the single newline
to the start of the quoted text on the last line, for example.
If you do need to flush the buffer above, you can send an endl if you also need a newline, or just flush the buffer yourself:
output << ...... << flush;
output.flush();

// can use std::flush manipulator
// or call a member fn

On the other hand, there are times when writing to a file should be like writing to standard error; no buffering should be done
because the data needs to appear quickly (a prime example is a log file for security-related information). The way to do this is
just to turn off the buffering before any I/O operations at all have been done (note that opening counts as an I/O operation):
std::ofstream
std::ifstream
int
i;

os;
is;

os.rdbuf()->pubsetbuf(0,0);
is.rdbuf()->pubsetbuf(0,0);
os.open("/foo/bar/baz");
is.open("/qux/quux/quuux");
...
os << "this data is written immediately\n";
is >> i;
// and this will probably cause a disk read

Since all aspects of buffering are handled by a streambuf-derived member, it is necessary to get at that member with rdbuf().
Then the public version of setbuf can be called. The arguments are the same as those for the Standard C I/O Library function
(a buffer area followed by its size).
A great deal of this is implementation-dependent. For example, streambuf does not specify any actions for its own setbu
f()-ish functions; the classes derived from streambuf each define behavior that "makes sense" for that class: an argument of
(0,0) turns off buffering for filebuf but does nothing at all for its siblings stringbuf and strstreambuf, and specifying
anything other than (0,0) has varying effects. User-defined classes derived from streambuf can do whatever they want. (For
filebuf and arguments for (p,s) other than zeros, libstdc++ does what you’d expect: the first s bytes of p are used as a
buffer, which you must allocate and deallocate.)
A last reminder: there are usually more buffers involved than just those at the language/library level. Kernel buffers, disk buffers,
and the like will also have an effect. Inspecting and changing those are system-dependent.

13.3

Memory Based Streams

13.3.1

Compatibility With strstream

Stringstreams (defined in the header ) are in this author’s opinion one of the coolest things since sliced time. An
example of their use is in the Received Wisdom section for Sect1 21 (Strings), describing how to format strings.
The quick definition is: they are siblings of ifstream and ofstream, and they do for std::string what their siblings do for
files. All that work you put into writing << and >> functions for your classes now pays off again! Need to format a string before
passing the string to a function? Send your stuff via << to an ostringstream. You’ve read a string as input and need to parse it?
Initialize an istringstream with that string, and then pull pieces out of it with >>. Have a stringstream and need to get a copy of
the string inside? Just call the str() member function.
This only works if you’ve written your <> functions correctly, though, and correctly means that they take istreams and
ostreams as parameters, not if streams and of streams. If they take the latter, then your I/O operators will work fine with file
streams, but with nothing else -- including stringstreams.
If you are a user of the strstream classes, you need to update your code. You don’t have to explicitly append ends to terminate
the C-style character array, you don’t have to mess with "freezing" functions, and you don’t have to manage the memory yourself.
The strstreams have been officially deprecated, which means that 1) future revisions of the C++ Standard won’t support them,
and 2) if you use them, people will laugh at you.

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File Based Streams

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Copying a File

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So you want to copy a file quickly and easily, and most important, completely portably. And since this is C++, you have an open
ifstream (call it IN) and an open ofstream (call it OUT):
#include 
std::ifstream
std::ofstream

IN ("input_file");
OUT ("output_file");

Here’s the easiest way to get it completely wrong:
OUT << IN;

For those of you who don’t already know why this doesn’t work (probably from having done it before), I invite you to quickly
create a simple text file called "input_file" containing the sentence
The quick brown fox jumped over the lazy dog.

surrounded by blank lines. Code it up and try it. The contents of "output_file" may surprise you.
Seriously, go do it. Get surprised, then come back. It’s worth it.
The thing to remember is that the basic_[io]stream classes handle formatting, nothing else. In particular, they break up
on whitespace. The actual reading, writing, and storing of data is handled by the basic_streambuf family. Fortunately, the
operator<< is overloaded to take an ostream and a pointer-to-streambuf, in order to help with just this kind of "dump the data
verbatim" situation.
Why a pointer to streambuf and not just a streambuf? Well, the [io]streams hold pointers (or references, depending on the
implementation) to their buffers, not the actual buffers. This allows polymorphic behavior on the chapter of the buffers as well
as the streams themselves. The pointer is easily retrieved using the rdbuf() member function. Therefore, the easiest way to
copy the file is:
OUT << IN.rdbuf();

So what was happening with OUT<> operators of the normal fstreams
to do binary I/O.
Sorry. Them’s the breaks.
This isn’t going to try and be a complete tutorial on reading and writing binary files (because "binary" covers a lot of ground),
but we will try and clear up a couple of misconceptions and common errors.
First, ios::binary has exactly one defined effect, no more and no less. Normal text mode has to be concerned with the
newline characters, and the runtime system will translate between (for example) ’\n’ and the appropriate end-of-line sequence
(LF on Unix, CRLF on DOS, CR on Macintosh, etc). (There are other things that normal mode does, but that’s the most obvious.)

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Opening a file in binary mode disables this conversion, so reading a CRLF sequence under Windows won’t accidentally get
mapped to a ’\n’ character, etc. Binary mode is not supposed to suddenly give you a bitstream, and if it is doing so in your
program then you’ve discovered a bug in your vendor’s compiler (or some other chapter of the C++ implementation, possibly the
runtime system).
Second, using << to write and >> to read isn’t going to work with the standard file stream classes, even if you use skipws
during reading. Why not? Because ifstream and ofstream exist for the purpose of formatting, not reading and writing. Their job
is to interpret the data into text characters, and that’s exactly what you don’t want to happen during binary I/O.
Third, using the get() and put()/write() member functions still aren’t guaranteed to help you. These are "unformatted"
I/O functions, but still character-based. (This may or may not be what you want, see below.)
Notice how all the problems here are due to the inappropriate use of formatting functions and classes to perform something which
requires that formatting not be done? There are a seemingly infinite number of solutions, and a few are listed here:
• “Derive your own fstream-type classes and write your own <> operators to do binary I/O on whatever data types you’re
using.”
This is a Bad Thing, because while the compiler would probably be just fine with it, other humans are going to be confused.
The overloaded bitshift operators have a well-defined meaning (formatting), and this breaks it.
• “Build the file structure in memory, then mmap() the file and copy the structure. ”
Well, this is easy to make work, and easy to break, and is pretty equivalent to using ::read() and ::write() directly, and
makes no use of the iostream library at all...
• “Use streambufs, that’s what they’re there for.”
While not trivial for the beginner, this is the best of all solutions. The streambuf/filebuf layer is the layer that is responsible for
actual I/O. If you want to use the C++ library for binary I/O, this is where you start.
How to go about using streambufs is a bit beyond the scope of this document (at least for now), but while streambufs go a long
way, they still leave a couple of things up to you, the programmer. As an example, byte ordering is completely between you and
the operating system, and you have to handle it yourself.
Deriving a streambuf or filebuf class from the standard ones, one that is specific to your data types (or an abstraction thereof)
is probably a good idea, and lots of examples exist in journals and on Usenet. Using the standard filebufs directly (either by
declaring your own or by using the pointer returned from an fstream’s rdbuf()) is certainly feasible as well.
One area that causes problems is trying to do bit-by-bit operations with filebufs. C++ is no different from C in this respect: I/O
must be done at the byte level. If you’re trying to read or write a few bits at a time, you’re going about it the wrong way. You
must read/write an integral number of bytes and then process the bytes. (For example, the streambuf functions take and return
variables of type int_type.)
Another area of problems is opening text files in binary mode. Generally, binary mode is intended for binary files, and opening
text files in binary mode means that you now have to deal with all of those end-of-line and end-of-file problems that we mentioned
before.
An instructive thread from comp.lang.c++.moderated delved off into this topic starting more or less at this post and continuing
to the end of the thread. (The subject heading is "binary iostreams" on both comp.std.c++ and comp.lang.c++.moderated.) Take
special note of the replies by James Kanze and Dietmar Kühl.
Briefly, the problems of byte ordering and type sizes mean that the unformatted functions like ostream::put() and istr
eam::get() cannot safely be used to communicate between arbitrary programs, or across a network, or from one invocation
of a program to another invocation of the same program on a different platform, etc.

13.5

Interacting with C

13.5.1

Using FILE* and file descriptors

See the extensions for using FILE and file descriptors with ofstream and ifstream.

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Performance

Pathetic Performance? Ditch C.
It sounds like a flame on C, but it isn’t. Really. Calm down. I’m just saying it to get your attention.
Because the C++ library includes the C library, both C-style and C++-style I/O have to work at the same time. For example:
#include 
#include 
std::cout << "Hel";
std::printf ("lo, worl");
std::cout << "d!\n";

This must do what you think it does.
Alert members of the audience will immediately notice that buffering is going to make a hash of the output unless special steps
are taken.
The special steps taken by libstdc++, at least for version 3.0, involve doing very little buffering for the standard streams, leaving
most of the buffering to the underlying C library. (This kind of thing is tricky to get right.) The upside is that correctness is
ensured. The downside is that writing through cout can quite easily lead to awful performance when the C++ I/O library is
layered on top of the C I/O library (as it is for 3.0 by default). Some patches have been applied which improve the situation for
3.1.
However, the C and C++ standard streams only need to be kept in sync when both libraries’ facilities are in use. If your program
only uses C++ I/O, then there’s no need to sync with the C streams. The right thing to do in this case is to call
#include any of the I/O headers such as ios, iostream, etc
std::ios::sync_with_stdio(false);

You must do this before performing any I/O via the C++ stream objects. Once you call this, the C++ streams will operate
independently of the (unused) C streams. For GCC 3.x, this means that cout and company will become fully buffered on their
own.
Note, by the way, that the synchronization requirement only applies to the standard streams (cin, cout, cerr, clog, and their
wide-character counterparts). File stream objects that you declare yourself have no such requirement and are fully buffered.

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Chapter 14

Atomics
Facilities for atomic operations.

14.1

API Reference

All items are declared in the standard header file atomic.
Set of typedefs that map int to atomic_int, and so on for all builtin integral types. Global enumeration memory_order to
control memory ordering. Also includes atomic, a class template with member functions such as load and store that is
instantiable such that atomic_int is the base class of atomic.
Full API details.

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Chapter 15

Concurrency
Facilities for concurrent operation, and control thereof.

15.1

API Reference

All items are declared in one of four standard header files.
In header mutex, class template mutex and variants, class once_flag, and class template unique_lock.
In header condition_variable, classes condition_variable and condition_variable_any.
In header thread, class thread and namespace this_thread.
In header future, class template future and class template shared_future, class template promise, and packaged_
task.
Full API details.

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Part III

Extensions

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Here we will make an attempt at describing the non-Standard extensions to the library. Some of these are from older versions of
standard library components, namely SGI’s STL, and some of these are GNU’s.
Before you leap in and use any of these extensions, be aware of two things:
1. Non-Standard means exactly that.
The behavior, and the very existence, of these extensions may change with little or no warning. (Ideally, the really good
ones will appear in the next revision of C++.) Also, other platforms, other compilers, other versions of g++ or libstdc++
may not recognize these names, or treat them differently, or...
2. You should know how to access these headers properly.

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Chapter 16

Compile Time Checks
Also known as concept checking.
In 1999, SGI added concept checkers to their implementation of the STL: code which checked the template parameters of
instantiated pieces of the STL, in order to insure that the parameters being used met the requirements of the standard. For
example, the Standard requires that types passed as template parameters to vector be “Assignable” (which means what you
think it means). The checking was done during compilation, and none of the code was executed at runtime.
Unfortunately, the size of the compiler files grew significantly as a result. The checking code itself was cumbersome. And bugs
were found in it on more than one occasion.
The primary author of the checking code, Jeremy Siek, had already started work on a replacement implementation. The new
code has been formally reviewed and accepted into the Boost libraries, and we are pleased to incorporate it into the GNU C++
library.
The new version imposes a much smaller space overhead on the generated object file. The checks are also cleaner and easier to
read and understand.
They are off by default for all versions of GCC from 3.0 to 3.4 (the latest release at the time of writing). They can be
enabled at configure time with --enable-concept-checks. You can enable them on a per-translation-unit basis with #define
_GLIBCXX_CONCEPT_CHECKS for GCC 3.4 and higher (or with #define _GLIBCPP_CONCEPT_CHECKS for versions
3.1, 3.2 and 3.3).
Please note that the concept checks only validate the requirements of the old C++03 standard. C++11 was expected to have
first-class support for template parameter constraints based on concepts in the core language. This would have obviated the need
for the library-simulated concept checking described above, but was not part of C++11.

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Chapter 17

Debug Mode
17.1

Intro

By default, libstdc++ is built with efficiency in mind, and therefore performs little or no error checking that is not required by the
C++ standard. This means that programs that incorrectly use the C++ standard library will exhibit behavior that is not portable
and may not even be predictable, because they tread into implementation-specific or undefined behavior. To detect some of these
errors before they can become problematic, libstdc++ offers a debug mode that provides additional checking of library facilities,
and will report errors in the use of libstdc++ as soon as they can be detected by emitting a description of the problem to standard
error and aborting the program. This debug mode is available with GCC 3.4.0 and later versions.
The libstdc++ debug mode performs checking for many areas of the C++ standard, but the focus is on checking interactions
among standard iterators, containers, and algorithms, including:
• Safe iterators: Iterators keep track of the container whose elements they reference, so errors such as incrementing a past-the-end
iterator or dereferencing an iterator that points to a container that has been destructed are diagnosed immediately.
• Algorithm preconditions: Algorithms attempt to validate their input parameters to detect errors as early as possible. For
instance, the set_intersection algorithm requires that its iterator parameters first1 and last1 form a valid iterator
range, and that the sequence [first1, last1) is sorted according to the same predicate that was passed to set_interse
ction; the libstdc++ debug mode will detect an error if the sequence is not sorted or was sorted by a different predicate.

17.2

Semantics

A program that uses the C++ standard library correctly will maintain the same semantics under debug mode as it had with the
normal (release) library. All functional and exception-handling guarantees made by the normal library also hold for the debug
mode library, with one exception: performance guarantees made by the normal library may not hold in the debug mode library.
For instance, erasing an element in a std::list is a constant-time operation in normal library, but in debug mode it is linear
in the number of iterators that reference that particular list. So while your (correct) program won’t change its results, it is likely
to execute more slowly.
libstdc++ includes many extensions to the C++ standard library. In some cases the extensions are obvious, such as the hashed
associative containers, whereas other extensions give predictable results to behavior that would otherwise be undefined, such
as throwing an exception when a std::basic_string is constructed from a NULL character pointer. This latter category
also includes implementation-defined and unspecified semantics, such as the growth rate of a vector. Use of these extensions
is not considered incorrect, so code that relies on them will not be rejected by debug mode. However, use of these extensions
may affect the portability of code to other implementations of the C++ standard library, and is therefore somewhat hazardous.
For this reason, the libstdc++ debug mode offers a "pedantic" mode (similar to GCC’s -pedantic compiler flag) that attempts
to emulate the semantics guaranteed by the C++ standard. For instance, constructing a std::basic_string with a NULL
character pointer would result in an exception under normal mode or non-pedantic debug mode (this is a libstdc++ extension),
whereas under pedantic debug mode libstdc++ would signal an error. To enable the pedantic debug mode, compile your program

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with both -D_GLIBCXX_DEBUG and -D_GLIBCXX_DEBUG_PEDANTIC . (N.B. In GCC 3.4.x and 4.0.0, due to a bug, D_GLIBXX_DEBUG_PEDANTIC was also needed. The problem has been fixed in GCC 4.0.1 and later versions.)
The following library components provide extra debugging capabilities in debug mode:
• std::basic_string (no safe iterators and see note below)
• std::bitset
• std::deque
• std::list
• std::map
• std::multimap
• std::multiset
• std::set
• std::vector
• std::unordered_map
• std::unordered_multimap
• std::unordered_set
• std::unordered_multiset
N.B. although there are precondition checks for some string operations, e.g. operator[], they will not always be run when
using the char and wchar_t specialisations (std::string and std::wstring). This is because libstdc++ uses GCC’s
extern template extension to provide explicit instantiations of std::string and std::wstring, and those explicit
instantiations don’t include the debug-mode checks. If the containing functions are inlined then the checks will run, so compiling
with -O1 might be enough to enable them. Alternatively -D_GLIBCXX_EXTERN_TEMPLATE=0 will suppress the declarations of the explicit instantiations and cause the functions to be instantiated with the debug-mode checks included, but this is
unsupported and not guaranteed to work. For full debug-mode support you can use the __gnu_debug::basic_string
debugging container directly, which always works correctly.

17.3

Using

17.3.1

Using the Debug Mode

To use the libstdc++ debug mode, compile your application with the compiler flag -D_GLIBCXX_DEBUG. Note that this flag
changes the sizes and behavior of standard class templates such as std::vector, and therefore you can only link code
compiled with debug mode and code compiled without debug mode if no instantiation of a container is passed between the two
translation units.
By default, error messages are formatted to fit on lines of about 78 characters. The environment variable GLIBCXX_DEBUG_M
ESSAGE_LENGTH can be used to request a different length.

17.3.2

Using a Specific Debug Container

When it is not feasible to recompile your entire application, or only specific containers need checking, debugging containers are
available as GNU extensions. These debugging containers are functionally equivalent to the standard drop-in containers used in
debug mode, but they are available in a separate namespace as GNU extensions and may be used in programs compiled with
either release mode or with debug mode. The following table provides the names and headers of the debugging containers:
In addition, when compiling in C++11 mode, these additional containers have additional debug capability.

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Container

Header

std::bitset

bitset

std::deque
std::list
std::map

deque
list
map

std::multimap

map

std::multiset

set

std::set

set

std::string

string

std::wstring

string

std::basic_string

string

std::vector

vector

Debug container
__gnu_debug::
bitset
__gnu_debug::deque
__gnu_debug::list
__gnu_debug::map
__gnu_debug::
multimap
__gnu_debug::
multiset
__gnu_debug::set
__gnu_debug::
string
__gnu_debug::
wstring
__gnu_debug::
basic_string
__gnu_debug::
vector

Debug header












Table 17.1: Debugging Containers

Container

Header

std::unordered_map

unordered_map

std::
unordered_multimap

unordered_map

std::unordered_set

unordered_set

std::
unordered_multiset

unordered_set

Debug container
__gnu_debug::
unordered_map
__gnu_debug::
unordered_multimap
__gnu_debug::
unordered_set
__gnu_debug::
unordered_multiset

Table 17.2: Debugging Containers C++11

Debug header





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Design

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Goals

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The libstdc++ debug mode replaces unsafe (but efficient) standard containers and iterators with semantically equivalent safe
standard containers and iterators to aid in debugging user programs. The following goals directed the design of the libstdc++
debug mode:
• Correctness: the libstdc++ debug mode must not change the semantics of the standard library for all cases specified in the
ANSI/ISO C++ standard. The essence of this constraint is that any valid C++ program should behave in the same manner
regardless of whether it is compiled with debug mode or release mode. In particular, entities that are defined in namespace std
in release mode should remain defined in namespace std in debug mode, so that legal specializations of namespace std entities
will remain valid. A program that is not valid C++ (e.g., invokes undefined behavior) is not required to behave similarly,
although the debug mode will abort with a diagnostic when it detects undefined behavior.
• Performance: the additional of the libstdc++ debug mode must not affect the performance of the library when it is compiled in
release mode. Performance of the libstdc++ debug mode is secondary (and, in fact, will be worse than the release mode).
• Usability: the libstdc++ debug mode should be easy to use. It should be easily incorporated into the user’s development
environment (e.g., by requiring only a single new compiler switch) and should produce reasonable diagnostics when it detects
a problem with the user program. Usability also involves detection of errors when using the debug mode incorrectly, e.g., by
linking a release-compiled object against a debug-compiled object if in fact the resulting program will not run correctly.
• Minimize recompilation: While it is expected that users recompile at least part of their program to use debug mode, the amount
of recompilation affects the detect-compile-debug turnaround time. This indirectly affects the usefulness of the debug mode,
because debugging some applications may require rebuilding a large amount of code, which may not be feasible when the
suspect code may be very localized. There are several levels of conformance to this requirement, each with its own usability
and implementation characteristics. In general, the higher-numbered conformance levels are more usable (i.e., require less
recompilation) but are more complicated to implement than the lower-numbered conformance levels.
1. Full recompilation: The user must recompile his or her entire application and all C++ libraries it depends on, including
the C++ standard library that ships with the compiler. This must be done even if only a small part of the program can use
debugging features.
2. Full user recompilation: The user must recompile his or her entire application and all C++ libraries it depends on, but
not the C++ standard library itself. This must be done even if only a small part of the program can use debugging
features. This can be achieved given a full recompilation system by compiling two versions of the standard library when
the compiler is installed and linking against the appropriate one, e.g., a multilibs approach.
3. Partial recompilation: The user must recompile the parts of his or her application and the C++ libraries it depends on
that will use the debugging facilities directly. This means that any code that uses the debuggable standard containers
would need to be recompiled, but code that does not use them (but may, for instance, use IOStreams) would not have to
be recompiled.
4. Per-use recompilation: The user must recompile the parts of his or her application and the C++ libraries it depends on
where debugging should occur, and any other code that interacts with those containers. This means that a set of translation
units that accesses a particular standard container instance may either be compiled in release mode (no checking) or
debug mode (full checking), but must all be compiled in the same way; a translation unit that does not see that standard
container instance need not be recompiled. This also means that a translation unit A that contains a particular instantiation
(say, std::vector) compiled in release mode can be linked against a translation unit B that contains the same
instantiation compiled in debug mode (a feature not present with partial recompilation). While this behavior is technically
a violation of the One Definition Rule, this ability tends to be very important in practice. The libstdc++ debug mode
supports this level of recompilation.
5. Per-unit recompilation: The user must only recompile the translation units where checking should occur, regardless of
where debuggable standard containers are used. This has also been dubbed "-g mode", because the -g compiler switch
works in this way, emitting debugging information at a per--translation-unit granularity. We believe that this level of
recompilation is in fact not possible if we intend to supply safe iterators, leave the program semantics unchanged, and
not regress in performance under release mode because we cannot associate extra information with an iterator (to form
a safe iterator) without either reserving that space in release mode (performance regression) or allocating extra memory
associated with each iterator with new (changes the program semantics).

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Methods

This section provides an overall view of the design of the libstdc++ debug mode and details the relationship between design
decisions and the stated design goals.
17.4.2.1

The Wrapper Model

The libstdc++ debug mode uses a wrapper model where the debugging versions of library components (e.g., iterators and containers) form a layer on top of the release versions of the library components. The debugging components first verify that the
operation is correct (aborting with a diagnostic if an error is found) and will then forward to the underlying release-mode container that will perform the actual work. This design decision ensures that we cannot regress release-mode performance (because
the release-mode containers are left untouched) and partially enables mixing debug and release code at link time, although that
will not be discussed at this time.
Two types of wrappers are used in the implementation of the debug mode: container wrappers and iterator wrappers. The two
types of wrappers interact to maintain relationships between iterators and their associated containers, which are necessary to
detect certain types of standard library usage errors such as dereferencing past-the-end iterators or inserting into a container
using an iterator from a different container.
17.4.2.1.1

Safe Iterators

Iterator wrappers provide a debugging layer over any iterator that is attached to a particular container, and will manage the
information detailing the iterator’s state (singular, dereferenceable, etc.) and tracking the container to which the iterator is
attached. Because iterators have a well-defined, common interface the iterator wrapper is implemented with the iterator adaptor
class template __gnu_debug::_Safe_iterator, which takes two template parameters:
• Iterator: The underlying iterator type, which must be either the iterator or const_iterator typedef from the
sequence type this iterator can reference.
• Sequence: The type of sequence that this iterator references. This sequence must be a safe sequence (discussed below)
whose iterator or const_iterator typedef is the type of the safe iterator.
17.4.2.1.2

Safe Sequences (Containers)

Container wrappers provide a debugging layer over a particular container type. Because containers vary greatly in the member
functions they support and the semantics of those member functions (especially in the area of iterator invalidation), container
wrappers are tailored to the container they reference, e.g., the debugging version of std::list duplicates the entire interface
of std::list, adding additional semantic checks and then forwarding operations to the real std::list (a public base
class of the debugging version) as appropriate. However, all safe containers inherit from the class template __gnu_debug:
:_Safe_sequence, instantiated with the type of the safe container itself (an instance of the curiously recurring template
pattern).
The iterators of a container wrapper will be safe iterators that reference sequences of this type and wrap the iterators provided by
the release-mode base class. The debugging container will use only the safe iterators within its own interface (therefore requiring
the user to use safe iterators, although this does not change correct user code) and will communicate with the release-mode base
class with only the underlying, unsafe, release-mode iterators that the base class exports.
The debugging version of std::list will have the following basic structure:
template
class debug-list :
public release-list<_Tp, _Allocator>,
public __gnu_debug::_Safe_sequence >
{
typedef release-list<_Tp, _Allocator> _Base;
typedef debug-list<_Tp, _Allocator>
_Self;
public:

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typedef __gnu_debug::_Safe_iterator
iterator;
typedef __gnu_debug::_Safe_iterator ←const_iterator;
// duplicate std::list interface with debugging semantics
};

17.4.2.2

Precondition Checking

The debug mode operates primarily by checking the preconditions of all standard library operations that it supports. Preconditions
that are always checked (regardless of whether or not we are in debug mode) are checked via the __check_xxx macros defined
and documented in the source file include/debug/debug.h. Preconditions that may or may not be checked, depending
on the debug-mode macro _GLIBCXX_DEBUG, are checked via the __requires_xxx macros defined and documented in
the same source file. Preconditions are validated using any additional information available at run-time, e.g., the containers that
are associated with a particular iterator, the position of the iterator within those containers, the distance between two iterators
that may form a valid range, etc. In the absence of suitable information, e.g., an input iterator that is not a safe iterator, these
precondition checks will silently succeed.
The majority of precondition checks use the aforementioned macros, which have the secondary benefit of having prewritten
debug messages that use information about the current status of the objects involved (e.g., whether an iterator is singular or what
sequence it is attached to) along with some static information (e.g., the names of the function parameters corresponding to the
objects involved). When not using these macros, the debug mode uses either the debug-mode assertion macro _GLIBCXX_DEB
UG_ASSERT , its pedantic cousin _GLIBCXX_DEBUG_PEDASSERT, or the assertion check macro that supports more advance
formulation of error messages, _GLIBCXX_DEBUG_VERIFY. These macros are documented more thoroughly in the debug
mode source code.
17.4.2.3

Release- and debug-mode coexistence

The libstdc++ debug mode is the first debug mode we know of that is able to provide the "Per-use recompilation" (4) guarantee,
that allows release-compiled and debug-compiled code to be linked and executed together without causing unpredictable behavior. This guarantee minimizes the recompilation that users are required to perform, shortening the detect-compile-debug bug
hunting cycle and making the debug mode easier to incorporate into development environments by minimizing dependencies.
Achieving link- and run-time coexistence is not a trivial implementation task. To achieve this goal we use inline namespaces and
a complex organization of debug- and release-modes. The end result is that we have achieved per-use recompilation but have had
to give up some checking of the std::basic_string class template (namely, safe iterators).
17.4.2.3.1

Compile-time coexistence of release- and debug-mode components

Both the release-mode components and the debug-mode components need to exist within a single translation unit so that the
debug versions can wrap the release versions. However, only one of these components should be user-visible at any particular
time with the standard name, e.g., std::list.
In release mode, we define only the release-mode version of the component with its standard name and do not include the
debugging component at all. The release mode version is defined within the namespace std. Minus the namespace associations,
this method leaves the behavior of release mode completely unchanged from its behavior prior to the introduction of the libstdc++
debug mode. Here’s an example of what this ends up looking like, in C++.
namespace std
{
template >
class list
{
// ...
};
} // namespace std

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In debug mode we include the release-mode container (which is now defined in the namespace __cxx1998) and also the debugmode container. The debug-mode container is defined within the namespace __debug, which is associated with namespace
std via the C++11 namespace association language feature. This method allows the debug and release versions of the same
component to coexist at compile-time and link-time without causing an unreasonable maintenance burden, while minimizing
confusion. Again, this boils down to C++ code as follows:
namespace std
{
namespace __cxx1998
{
template >
class list
{
// ...
};
} // namespace __gnu_norm
namespace __debug
{
template >
class list
: public __cxx1998::list<_Tp, _Alloc>,
public __gnu_debug::_Safe_sequence >
{
// ...
};
} // namespace __cxx1998
inline namespace __debug { }
}

17.4.2.3.2

Link- and run-time coexistence of release- and debug-mode components

Because each component has a distinct and separate release and debug implementation, there is no issue with link-time coexistence: the separate namespaces result in different mangled names, and thus unique linkage.
However, components that are defined and used within the C++ standard library itself face additional constraints. For instance,
some of the member functions of std::moneypunct return std::basic_string. Normally, this is not a problem, but
with a mixed mode standard library that could be using either debug-mode or release-mode basic_string objects, things
get more complicated. As the return value of a function is not encoded into the mangled name, there is no way to specify a
release-mode or a debug-mode string. In practice, this results in runtime errors. A simplified example of this problem is as
follows.
Take this translation unit, compiled in debug-mode:
// -D_GLIBCXX_DEBUG
#include 
std::string test02();
std::string test01()
{
return test02();
}
int main()
{
test01();
return 0;
}

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... and linked to this translation unit, compiled in release mode:
#include 
std::string
test02()
{
return std::string("toast");
}

For this reason we cannot easily provide safe iterators for the std::basic_string class template, as it is present throughout
the C++ standard library. For instance, locale facets define typedefs that include basic_string: in a mixed debug/release
program, should that typedef be based on the debug-mode basic_string or the release-mode basic_string? While the
answer could be "both", and the difference hidden via renaming a la the debug/release containers, we must note two things about
locale facets:
1. They exist as shared state: one can create a facet in one translation unit and access the facet via the same type name in a
different translation unit. This means that we cannot have two different versions of locale facets, because the types would
not be the same across debug/release-mode translation unit barriers.
2. They have virtual functions returning strings: these functions mangle in the same way regardless of the mangling of their
return types (see above), and their precise signatures can be relied upon by users because they may be overridden in derived
classes.
With the design of libstdc++ debug mode, we cannot effectively hide the differences between debug and release-mode strings
from the user. Failure to hide the differences may result in unpredictable behavior, and for this reason we have opted to only
perform basic_string changes that do not require ABI changes. The effect on users is expected to be minimal, as there are
simple alternatives (e.g., __gnu_debug::basic_string), and the usability benefit we gain from the ability to mix debugand release-compiled translation units is enormous.
17.4.2.3.3

Alternatives for Coexistence

The coexistence scheme above was chosen over many alternatives, including language-only solutions and solutions that also
required extensions to the C++ front end. The following is a partial list of solutions, with justifications for our rejection of each.
• Completely separate debug/release libraries: This is by far the simplest implementation option, where we do not allow any
coexistence of debug- and release-compiled translation units in a program. This solution has an extreme negative affect on
usability, because it is quite likely that some libraries an application depends on cannot be recompiled easily. This would not
meet our usability or minimize recompilation criteria well.
• Add a Debug boolean template parameter: Partial specialization could be used to select the debug implementation when
Debug ==true, and the state of _GLIBCXX_DEBUG could decide whether the default Debug argument is true or false.
This option would break conformance with the C++ standard in both debug and release modes. This would not meet our
correctness criteria.
• Packaging a debug flag in the allocators: We could reuse the Allocator template parameter of containers by adding a
sentinel wrapper debug<> that signals the user’s intention to use debugging, and pick up the debug<> allocator wrapper in a
partial specialization. However, this has two drawbacks: first, there is a conformance issue because the default allocator would
not be the standard-specified std::allocator. Secondly (and more importantly), users that specify allocators instead
of implicitly using the default allocator would not get debugging containers. Thus this solution fails the correctness criteria.
• Define debug containers in another namespace, and employ a using declaration (or directive): This is an enticing option,
because it would eliminate the need for the link_name extension by aliasing the templates. However, there is no true template
aliasing mechanism in C++, because both using directives and using declarations disallow specialization. This method fails
the correctness criteria.
• Use implementation-specific properties of anonymous namespaces. See this post. This method fails the correctness criteria.

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• Extension: allow reopening on namespaces: This would allow the debug mode to effectively alias the namespace std to an
internal namespace, such as __gnu_std_debug, so that it is completely separate from the release-mode std namespace.
While this will solve some renaming problems and ensure that debug- and release-compiled code cannot be mixed unsafely, it
ensures that debug- and release-compiled code cannot be mixed at all. For instance, the program would have two std::cout
objects! This solution would fails the minimize recompilation requirement, because we would only be able to support option
(1) or (2).
• Extension: use link name: This option involves complicated re-naming between debug-mode and release-mode components at
compile time, and then a g++ extension called link name to recover the original names at link time. There are two drawbacks to
this approach. One, it’s very verbose, relying on macro renaming at compile time and several levels of include ordering. Two,
ODR issues remained with container member functions taking no arguments in mixed-mode settings resulting in equivalent
link names, vector::push_back() being one example. See proof-of-concept using link name.
Other options may exist for implementing the debug mode, many of which have probably been considered and others that may
still be lurking. This list may be expanded over time to include other options that we could have implemented, but in all cases the
full ramifications of the approach (as measured against the design goals for a libstdc++ debug mode) should be considered first.
The DejaGNU testsuite includes some testcases that check for known problems with some solutions (e.g., the using declaration
solution that breaks user specialization), and additional testcases will be added as we are able to identify other typical problem
cases. These test cases will serve as a benchmark by which we can compare debug mode implementations.

17.4.3

Other Implementations

There are several existing implementations of debug modes for C++ standard library implementations, although none of them
directly supports debugging for programs using libstdc++. The existing implementations include:
• SafeSTL: SafeSTL was the original debugging version of the Standard Template Library (STL), implemented by Cay S.
Horstmann on top of the Hewlett-Packard STL. Though it inspired much work in this area, it has not been kept up-to-date for
use with modern compilers or C++ standard library implementations.
• STLport: STLport is a free implementation of the C++ standard library derived from the SGI implementation, and ported to
many other platforms. It includes a debug mode that uses a wrapper model (that in some ways inspired the libstdc++ debug
mode design), although at the time of this writing the debug mode is somewhat incomplete and meets only the "Full user
recompilation" (2) recompilation guarantee by requiring the user to link against a different library in debug mode vs. release
mode.
• Metrowerks CodeWarrior: The C++ standard library that ships with Metrowerks CodeWarrior includes a debug mode. It is a
full debug-mode implementation (including debugging for CodeWarrior extensions) and is easy to use, although it meets only
the "Full recompilation" (1) recompilation guarantee.

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Chapter 18

Parallel Mode
The libstdc++ parallel mode is an experimental parallel implementation of many algorithms the C++ Standard Library.
Several of the standard algorithms, for instance std::sort, are made parallel using OpenMP annotations. These parallel mode
constructs and can be invoked by explicit source declaration or by compiling existing sources with a specific compiler flag.

18.1

Intro

The following library components in the include numeric are included in the parallel mode:
• std::accumulate
• std::adjacent_difference
• std::inner_product
• std::partial_sum
The following library components in the include algorithm are included in the parallel mode:
• std::adjacent_find
• std::count
• std::count_if
• std::equal
• std::find
• std::find_if
• std::find_first_of
• std::for_each
• std::generate
• std::generate_n
• std::lexicographical_compare
• std::mismatch
• std::search

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• std::search_n
• std::transform
• std::replace
• std::replace_if
• std::max_element
• std::merge
• std::min_element
• std::nth_element
• std::partial_sort
• std::partition
• std::random_shuffle
• std::set_union
• std::set_intersection
• std::set_symmetric_difference
• std::set_difference
• std::sort
• std::stable_sort
• std::unique_copy

18.2

Semantics

The parallel mode STL algorithms are currently not exception-safe, i.e. user-defined functors must not throw exceptions. Also,
the order of execution is not guaranteed for some functions, of course. Therefore, user-defined functors should not have any
concurrent side effects.
Since the current GCC OpenMP implementation does not support OpenMP parallel regions in concurrent threads, it is not
possible to call parallel STL algorithm in concurrent threads, either. It might work with other compilers, though.

18.3

Using

18.3.1

Prerequisite Compiler Flags

Any use of parallel functionality requires additional compiler and runtime support, in particular support for OpenMP. Adding
this support is not difficult: just compile your application with the compiler flag -fopenmp. This will link in libgomp, the
GNU Offloading and Multi Processing Runtime Library, whose presence is mandatory.
In addition, hardware that supports atomic operations and a compiler capable of producing atomic operations is mandatory: GCC
defaults to no support for atomic operations on some common hardware architectures. Activating atomic operations may require
explicit compiler flags on some targets (like sparc and x86), such as -march=i686, -march=native or -mcpu=v9. See
the GCC manual for more information.

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Using Parallel Mode

To use the libstdc++ parallel mode, compile your application with the prerequisite flags as detailed above, and in addition
add -D_GLIBCXX_PARALLEL. This will convert all use of the standard (sequential) algorithms to the appropriate parallel
equivalents. Please note that this doesn’t necessarily mean that everything will end up being executed in a parallel manner, but
rather that the heuristics and settings coded into the parallel versions will be used to determine if all, some, or no algorithms will
be executed using parallel variants.
Note that the _GLIBCXX_PARALLEL define may change the sizes and behavior of standard class templates such as std::
search, and therefore one can only link code compiled with parallel mode and code compiled without parallel mode if no
instantiation of a container is passed between the two translation units. Parallel mode functionality has distinct linkage, and
cannot be confused with normal mode symbols.

18.3.3

Using Specific Parallel Components

When it is not feasible to recompile your entire application, or only specific algorithms need to be parallel-aware, individual
parallel algorithms can be made available explicitly. These parallel algorithms are functionally equivalent to the standard drop-in
algorithms used in parallel mode, but they are available in a separate namespace as GNU extensions and may be used in programs
compiled with either release mode or with parallel mode.
An example of using a parallel version of std::sort, but no other parallel algorithms, is:
#include 
#include 
int main()
{
std::vector v(100);
// ...
// Explicitly force a call to parallel sort.
__gnu_parallel::sort(v.begin(), v.end());
return 0;
}

Then compile this code with the prerequisite compiler flags (-fopenmp and any necessary architecture-specific flags for atomic
operations.)
The following table provides the names and headers of all the parallel algorithms that can be used in a similar manner:

18.4

Design

18.4.1

Interface Basics

All parallel algorithms are intended to have signatures that are equivalent to the ISO C++ algorithms replaced. For instance, the
std::adjacent_find function is declared as:
namespace std
{
template
_FIter
adjacent_find(_FIter, _FIter);
}

Which means that there should be something equivalent for the parallel version. Indeed, this is the case:

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Algorithm

Header

std::accumulate

numeric

std::adjacent_diff
erence

numeric

std::inner_product

numeric

std::partial_sum

numeric

std::adjacent_find

algorithm

std::count

algorithm

std::count_if

algorithm

std::equal

algorithm

std::find

algorithm

std::find_if

algorithm

std::find_first_of

algorithm

std::for_each

algorithm

std::generate

algorithm

std::generate_n

algorithm

std::lexicographic
al_compare

algorithm

std::mismatch

algorithm

std::search

algorithm

std::search_n

algorithm

std::transform

algorithm

std::replace

algorithm

std::replace_if

algorithm

std::max_element

algorithm

std::merge

algorithm

std::min_element

algorithm

std::nth_element

algorithm

std::partial_sort

algorithm

std::partition

algorithm

std::
random_shuffle

algorithm

std::set_union

algorithm

std::
set_intersection

algorithm

Parallel algorithm
__gnu_parallel::
accumulate
__gnu_parallel::
adjacent_differe
nce
__gnu_parallel::
inner_product
__gnu_parallel::
partial_sum
__gnu_parallel::
adjacent_find
__gnu_parallel::
count
__gnu_parallel::
count_if
__gnu_parallel::
equal
__gnu_parallel::
find
__gnu_parallel::
find_if
__gnu_parallel::
find_first_of
__gnu_parallel::
for_each
__gnu_parallel::
generate
__gnu_parallel::
generate_n
__gnu_parallel::
lexicographical_co
mpare
__gnu_parallel::
mismatch
__gnu_parallel::
search
__gnu_parallel::
search_n
__gnu_parallel::
transform
__gnu_parallel::
replace
__gnu_parallel::
replace_if
__gnu_parallel::
max_element
__gnu_parallel::
merge
__gnu_parallel::
min_element
__gnu_parallel::
nth_element
__gnu_parallel::
partial_sort
__gnu_parallel::
partition
__gnu_parallel::
random_shuffle
__gnu_parallel::
set_union
__gnu_parallel::
set_intersection

Parallel header
parallel/numeric
parallel/numeric
parallel/numeric
parallel/numeric
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm
parallel/algorithm

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namespace std
{
namespace __parallel
{
template
_FIter
adjacent_find(_FIter, _FIter);
...
}
}

But.... why the ellipses?
The ellipses in the example above represent additional overloads required for the parallel version of the function. These additional
overloads are used to dispatch calls from the ISO C++ function signature to the appropriate parallel function (or sequential
function, if no parallel functions are deemed worthy), based on either compile-time or run-time conditions.
The available signature options are specific for the different algorithms/algorithm classes.
The general view of overloads for the parallel algorithms look like this:
• ISO C++ signature
• ISO C++ signature + sequential_tag argument
• ISO C++ signature + algorithm-specific tag type (several signatures)
Please note that the implementation may use additional functions (designated with the _switch suffix) to dispatch from the
ISO C++ signature to the correct parallel version. Also, some of the algorithms do not have support for run-time conditions, so
the last overload is therefore missing.

18.4.2

Configuration and Tuning

18.4.2.1

Setting up the OpenMP Environment

Several aspects of the overall runtime environment can be manipulated by standard OpenMP function calls.
To specify the number of threads to be used for the algorithms globally, use the function omp_set_num_threads. An
example:
#include 
#include 
int main()
{
// Explicitly set number of threads.
const int threads_wanted = 20;
omp_set_dynamic(false);
omp_set_num_threads(threads_wanted);
// Call parallel mode algorithms.
return 0;
}

Some algorithms allow the number of threads being set for a particular call, by augmenting the algorithm variant. See the next
section for further information.
Other parts of the runtime environment able to be manipulated include nested parallelism (omp_set_nested), schedule kind
(omp_set_schedule), and others. See the OpenMP documentation for more information.

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Compile Time Switches

To force an algorithm to execute sequentially, even though parallelism is switched on in general via the macro _GLIBCXX_PAR
ALLEL, add __gnu_parallel::sequential_tag() to the end of the algorithm’s argument list.
Like so:
std::sort(v.begin(), v.end(), __gnu_parallel::sequential_tag());

Some parallel algorithm variants can be excluded from compilation by preprocessor defines. See the doxygen documentation on
compiletime_settings.h and features.h for details.
For some algorithms, the desired variant can be chosen at compile-time by appending a tag object. The available options are
specific to the particular algorithm (class).
For the "embarrassingly parallel" algorithms, there is only one "tag object type", the enum _Parallelism. It takes one of the following values, __gnu_parallel::parallel_tag, __gnu_parallel::balanced_tag, __gnu_parallel::unb
alanced_tag, __gnu_parallel::omp_loop_tag, __gnu_parallel::omp_loop_static_tag. This means
that the actual parallelization strategy is chosen at run-time. (Choosing the variants at compile-time will come soon.)
For the following algorithms in general, we have __gnu_parallel::parallel_tag and __gnu_parallel::defa
ult_parallel_tag, in addition to __gnu_parallel::sequential_tag. __gnu_parallel::default_para
llel_tag chooses the default algorithm at compiletime, as does omitting the tag. __gnu_parallel::parallel_tag
postpones the decision to runtime (see next section). For all tags, the number of threads desired for this call can optionally be
passed to the respective tag’s constructor.
The multiway_merge algorithm comes with the additional choices, __gnu_parallel::exact_tag and __gnu_par
allel::sampling_tag. Exact and sampling are the two available splitting strategies.
For the sort and stable_sort algorithms, there are several additional choices, namely __gnu_parallel::multiw
ay_mergesort_tag, __gnu_parallel::multiway_mergesort_exact_tag, __gnu_parallel::multiwa
y_mergesort_sampling_tag, __gnu_parallel::quicksort_tag, and __gnu_parallel::balanced_qui
cksort_tag. Multiway mergesort comes with the two splitting strategies for multi-way merging. The quicksort options cannot
be used for stable_sort.
18.4.2.3

Run Time Settings and Defaults

The default parallelization strategy, the choice of specific algorithm strategy, the minimum threshold limits for individual parallel
algorithms, and aspects of the underlying hardware can be specified as desired via manipulation of __gnu_parallel::
_Settings member data.
First off, the choice of parallelization strategy: serial, parallel, or heuristically deduced. This corresponds to __gnu_paral
lel::_Settings::algorithm_strategy and is a value of enum __gnu_parallel::_AlgorithmStrategy type. Choices
include: heuristic, force_sequential, and force_parallel. The default is heuristic.

Next, the sub-choices for algorithm variant, if not fixed at compile-time. Specific algorithms like find or sort can be implemented in multiple ways: when this is the case, a __gnu_parallel::_Settings member exists to pick the default strategy.
For example, __gnu_parallel::_Settings::sort_algorithm can have any values of enum __gnu_parallel::_SortAlgorithm
MWMS, QS, or QS_BALANCED.
Likewise for setting the minimal threshold for algorithm parallelization. Parallelism always incurs some overhead. Thus, it is
not helpful to parallelize operations on very small sets of data. Because of this, measures are taken to avoid parallelizing below
a certain, pre-determined threshold. For each algorithm, a minimum problem size is encoded as a variable in the active __gn
u_parallel::_Settings object. This threshold variable follows the following naming scheme: __gnu_parallel::
_Settings::[algorithm]_minimal_n. So, for fill, the threshold variable is __gnu_parallel::_Settings:
:fill_minimal_n,
Finally, hardware details like L1/L2 cache size can be hardwired via __gnu_parallel::_Settings::L1_cache_size
and friends.
All these configuration variables can be changed by the user, if desired. There exists one global instance of the class _Settings,
i. e. it is a singleton. It can be read and written by calling __gnu_parallel::_Settings::get and __gnu_paral

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lel::_Settings::set, respectively. Please note that the first call return a const object, so direct manipulation is forbidden.
See settings.h for complete details.
A small example of tuning the default:
#include 
#include 
int main()
{
__gnu_parallel::_Settings s;
s.algorithm_strategy = __gnu_parallel::force_parallel;
__gnu_parallel::_Settings::set(s);
// Do work... all algorithms will be parallelized, always.
return 0;
}

18.4.3

Implementation Namespaces

One namespace contain versions of code that are always explicitly sequential: __gnu_serial.
Two namespaces contain the parallel mode: std::__parallel and __gnu_parallel.
Parallel implementations of standard components, including template helpers to select parallelism, are defined in namespace
std::__parallel. For instance, std::transform from algorithm has a parallel counterpart in std::__paral
lel::transform from parallel/algorithm. In addition, these parallel implementations are injected into namespace
__gnu_parallel with using declarations.
Support and general infrastructure is in namespace __gnu_parallel.
More information, and an organized index of types and functions related to the parallel mode on a per-namespace basis, can be
found in the generated source documentation.

18.5

Testing

Both the normal conformance and regression tests and the supplemental performance tests work.
To run the conformance and regression tests with the parallel mode active,
make check-parallel

The log and summary files for conformance testing are in the testsuite/parallel directory.
To run the performance tests with the parallel mode active,
make check-performance-parallel

The result file for performance testing are in the testsuite directory, in the file libstdc++_performance.sum. In
addition, the policy-based containers have their own visualizations, which have additional software dependencies than the usual
bare-boned text file, and can be generated by using the make doc-performance rule in the testsuite’s Makefile.

18.6

Bibliography
[52] Johannes SinglerLeonor Frias, Copyright © 2007 , Workshop on Highly Parallel Processing on a Chip (HPPC)
2007. (LNCS) .
[53] Johannes SinglerPeter SandersFelix Putze, Copyright © 2007 , Euro-Par 2007: Parallel Processing. (LNCS
4641) .

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Chapter 19

Profile Mode
19.1

Intro

Goal: Give performance improvement advice based on recognition of suboptimal usage patterns of the standard library.
Method: Wrap the standard library code. Insert calls to an instrumentation library to record the internal state of various components at interesting entry/exit points to/from the standard library. Process trace, recognize suboptimal patterns, give advice. For
details, see the Perflint paper presented at CGO 2009.
Strengths:
• Unintrusive solution. The application code does not require any modification.
• The advice is call context sensitive, thus capable of identifying precisely interesting dynamic performance behavior.
• The overhead model is pay-per-view. When you turn off a diagnostic class at compile time, its overhead disappears.
Drawbacks:
• You must recompile the application code with custom options.
• You must run the application on representative input. The advice is input dependent.
• The execution time will increase, in some cases by factors.

19.1.1

Using the Profile Mode

This is the anticipated common workflow for program foo.cc:
$ cat foo.cc
#include 
int main() {
vector v;
for (int k = 0; k < 1024; ++k) v.insert(v.begin(), k);
}
$ g++ -D_GLIBCXX_PROFILE foo.cc
$ ./a.out
$ cat libstdcxx-profile.txt
vector-to-list: improvement = 5: call stack = 0x804842c ...
: advice = change std::vector to std::list
vector-size: improvement = 3: call stack = 0x804842c ...
: advice = change initial container size from 0 to 1024

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Anatomy of a warning:
• Warning id. This is a short descriptive string for the class that this warning belongs to. E.g., "vector-to-list".
• Estimated improvement. This is an approximation of the benefit expected from implementing the change suggested by the
warning. It is given on a log10 scale. Negative values mean that the alternative would actually do worse than the current
choice. In the example above, 5 comes from the fact that the overhead of inserting at the beginning of a vector vs. a list is
around 1024 * 1024 / 2, which is around 10e5. The improvement from setting the initial size to 1024 is in the range of 10e3,
since the overhead of dynamic resizing is linear in this case.
• Call stack. Currently, the addresses are printed without symbol name or code location attribution. Users are expected to
postprocess the output using, for instance, addr2line.
• The warning message. For some warnings, this is static text, e.g., "change vector to list". For other warnings, such as the one
above, the message contains numeric advice, e.g., the suggested initial size of the vector.
Three files are generated. libstdcxx-profile.txt contains human readable advice. libstdcxx-profile.raw contains implementation specific data about each diagnostic. Their format is not documented. They are sufficient to generate all the
advice given in libstdcxx-profile.txt. The advantage of keeping this raw format is that traces from multiple executions
can be aggregated simply by concatenating the raw traces. We intend to offer an external utility program that can issue advice
from a trace. libstdcxx-profile.conf.out lists the actual diagnostic parameters used. To alter parameters, edit this file
and rename it to libstdcxx-profile.conf.
Advice is given regardless whether the transformation is valid. For instance, we advise changing a map to an unordered_map even
if the application semantics require that data be ordered. We believe such warnings can help users understand the performance
behavior of their application better, which can lead to changes at a higher abstraction level.

19.1.2

Tuning the Profile Mode

Compile time switches and environment variables (see also file profiler.h). Unless specified otherwise, they can be set at compile
time using -D_ or by setting variable  in the environment where the program is run, before starting execution.
• _GLIBCXX_PROFILE_NO_: disable specific diagnostics. See section Diagnostics for possible values.
(Environment variables not supported.)
• _GLIBCXX_PROFILE_TRACE_PATH_ROOT: set an alternative root path for the output files.
• _GLIBCXX_PROFILE_MAX_WARN_COUNT: set it to the maximum number of warnings desired. The default value is 10.
• _GLIBCXX_PROFILE_MAX_STACK_DEPTH: if set to 0, the advice will be collected and reported for the program as a
whole, and not for each call context. This could also be used in continuous regression tests, where you just need to know
whether there is a regression or not. The default value is 32.
• _GLIBCXX_PROFILE_MEM_PER_DIAGNOSTIC: set a limit on how much memory to use for the accounting tables for
each diagnostic type. When this limit is reached, new events are ignored until the memory usage decreases under the limit.
Generally, this means that newly created containers will not be instrumented until some live containers are deleted. The default
is 128 MB.
• _GLIBCXX_PROFILE_NO_THREADS: Make the library not use threads. If thread local storage (TLS) is not available, you
will get a preprocessor error asking you to set -D_GLIBCXX_PROFILE_NO_THREADS if your program is single-threaded.
Multithreaded execution without TLS is not supported. (Environment variable not supported.)
• _GLIBCXX_HAVE_EXECINFO_H: This name should be defined automatically at library configuration time. If your library
was configured without execinfo.h, but you have it in your include path, you can define it explicitly. Without it, advice is
collected for the program as a whole, and not for each call context. (Environment variable not supported.)

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Code Location
libstdc++-v3/include/std/*
libstdc++-v3/include/profile/*
libstdc++-v3/include/profile/impl/*

Use
Preprocessor code to redirect to profile extension headers.
Profile extension public headers (map, vector, ...).
Profile extension internals. Implementation files are only
included from impl/profiler.h, which is the only file
included from the public headers.

Table 19.1: Profile Code Location

19.2

Design

19.2.1

Wrapper Model

In order to get our instrumented library version included instead of the release one, we use the same wrapper model as the debug
mode. We subclass entities from the release version. Wherever _GLIBCXX_PROFILE is defined, the release namespace is
std::__norm, whereas the profile namespace is std::__profile. Using plain std translates into std::__profile.
Whenever possible, we try to wrap at the public interface level, e.g., in unordered_set rather than in hashtable, in order
not to depend on implementation.
Mixing object files built with and without the profile mode must not affect the program execution. However, there are no guarantees to the accuracy of diagnostics when using even a single object not built with -D_GLIBCXX_PROFILE. Currently, mixing
the profile mode with debug and parallel extensions is not allowed. Mixing them at compile time will result in preprocessor
errors. Mixing them at link time is undefined.

19.2.2

Instrumentation

Instead of instrumenting every public entry and exit point, we chose to add instrumentation on demand, as needed by individual
diagnostics. The main reason is that some diagnostics require us to extract bits of internal state that are particular only to that
diagnostic. We plan to formalize this later, after we learn more about the requirements of several diagnostics.
All the instrumentation points can be switched on and off using -D[_NO]_GLIBCXX_PROFILE_ options.
With all the instrumentation calls off, there should be negligible overhead over the release version. This property is needed to
support diagnostics based on timing of internal operations. For such diagnostics, we anticipate turning most of the instrumentation
off in order to prevent profiling overhead from polluting time measurements, and thus diagnostics.
All the instrumentation on/off compile time switches live in include/profile/profiler.h.

19.2.3

Run Time Behavior

For practical reasons, the instrumentation library processes the trace partially rather than dumping it to disk in raw form. Each
event is processed when it occurs. It is usually attached a cost and it is aggregated into the database of a specific diagnostic class.
The cost model is based largely on the standard performance guarantees, but in some cases we use knowledge about GCC’s
standard library implementation.
Information is indexed by (1) call stack and (2) instance id or address to be able to understand and summarize precise creationuse-destruction dynamic chains. Although the analysis is sensitive to dynamic instances, the reports are only sensitive to call
context. Whenever a dynamic instance is destroyed, we accumulate its effect to the corresponding entry for the call stack of its
constructor location.
For details, see paper presented at CGO 2009.

19.2.4

Analysis and Diagnostics

Final analysis takes place offline, and it is based entirely on the generated trace and debugging info in the application binary. See
section Diagnostics for a list of analysis types that we plan to support.

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The input to the analysis is a table indexed by profile type and call stack. The data type for each entry depends on the profile
type.

19.2.5

Cost Model

While it is likely that cost models become complex as we get into more sophisticated analysis, we will try to follow a simple set
of rules at the beginning.
• Relative benefit estimation: The idea is to estimate or measure the cost of all operations in the original scenario versus the
scenario we advise to switch to. For instance, when advising to change a vector to a list, an occurrence of the insert method
will generally count as a benefit. Its magnitude depends on (1) the number of elements that get shifted and (2) whether it
triggers a reallocation.
• Synthetic measurements: We will measure the relative difference between similar operations on different containers. We plan
to write a battery of small tests that compare the times of the executions of similar methods on different containers. The idea is
to run these tests on the target machine. If this training phase is very quick, we may decide to perform it at library initialization
time. The results can be cached on disk and reused across runs.
• Timers: We plan to use timers for operations of larger granularity, such as sort. For instance, we can switch between different
sort methods on the fly and report the one that performs best for each call context.
• Show stoppers: We may decide that the presence of an operation nullifies the advice. For instance, when considering switching
from set to unordered_set, if we detect use of operator ++, we will simply not issue the advice, since this could signal
that the use care require a sorted container.

19.2.6

Reports

There are two types of reports. First, if we recognize a pattern for which we have a substitute that is likely to give better
performance, we print the advice and estimated performance gain. The advice is usually associated to a code position and
possibly a call stack.
Second, we report performance characteristics for which we do not have a clear solution for improvement. For instance, we can
point to the user the top 10 multimap locations which have the worst data locality in actual traversals. Although this does not
offer a solution, it helps the user focus on the key problems and ignore the uninteresting ones.

19.2.7

Testing

First, we want to make sure we preserve the behavior of the release mode. You can just type "make check-profile",
which builds and runs the whole test suite in profile mode.
Second, we want to test the correctness of each diagnostic. We created a profile directory in the test suite. Each diagnostic
must come with at least two tests, one for false positives and one for false negatives.

19.3

Extensions for Custom Containers

Many large projects use their own data structures instead of the ones in the standard library. If these data structures are similar
in functionality to the standard library, they can be instrumented with the same hooks that are used to instrument the standard
library. The instrumentation API is exposed in file profiler.h (look for "Instrumentation hooks").

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Empirical Cost Model

Currently, the cost model uses formulas with predefined relative weights for alternative containers or container implementations.
For instance, iterating through a vector is X times faster than iterating through a list.
(Under development.) We are working on customizing this to a particular machine by providing an automated way to compute
the actual relative weights for operations on the given machine.
(Under development.) We plan to provide a performance parameter database format that can be filled in either by hand or by an
automated training mechanism. The analysis module will then use this database instead of the built in. generic parameters.

19.5

Implementation Issues

19.5.1

Stack Traces

Accurate stack traces are needed during profiling since we group events by call context and dynamic instance. Without accurate
traces, diagnostics may be hard to interpret. For instance, when giving advice to the user it is imperative to reference application
code, not library code.
Currently we are using the libc backtrace routine to get stack traces. _GLIBCXX_PROFILE_STACK_DEPTH can be set to
0 if you are willing to give up call context information, or to a small positive value to reduce run time overhead.

19.5.2

Symbolization of Instruction Addresses

The profiling and analysis phases use only instruction addresses. An external utility such as addr2line is needed to postprocess
the result. We do not plan to add symbolization support in the profile extension. This would require access to symbol tables,
debug information tables, external programs or libraries and other system dependent information.

19.5.3

Concurrency

Our current model is simplistic, but precise. We cannot afford to approximate because some of our diagnostics require precise
matching of operations to container instance and call context. During profiling, we keep a single information table per diagnostic.
There is a single lock per information table.

19.5.4

Using the Standard Library in the Instrumentation Implementation

As much as we would like to avoid uses of libstdc++ within our instrumentation library, containers such as unordered_map are
very appealing. We plan to use them as long as they are named properly to avoid ambiguity.

19.5.5

Malloc Hooks

User applications/libraries can provide malloc hooks. When the implementation of the malloc hooks uses stdlibc++, there can be
an infinite cycle between the profile mode instrumentation and the malloc hook code.
We protect against reentrance to the profile mode instrumentation code, which should avoid this problem in most cases. The
protection mechanism is thread safe and exception safe. This mechanism does not prevent reentrance to the malloc hook itself,
which could still result in deadlock, if, for instance, the malloc hook uses non-recursive locks. XXX: A definitive solution to this
problem would be for the profile extension to use a custom allocator internally, and perhaps not to use libstdc++.

19.5.6

Construction and Destruction of Global Objects

The profiling library state is initialized at the first call to a profiling method. This allows us to record the construction of all
global objects. However, we cannot do the same at destruction time. The trace is written by a function registered by atexit,
thus invoked by exit.

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Developer Information

19.6.1

Big Picture

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The profile mode headers are included with -D_GLIBCXX_PROFILE through preprocessor directives in include/std/*.
Instrumented implementations are provided in include/profile/*. All instrumentation hooks are macros defined in inc
lude/profile/profiler.h.
All the implementation of the instrumentation hooks is in include/profile/impl/*. Although all the code gets included,
thus is publicly visible, only a small number of functions are called from outside this directory. All calls to hook implementations
must be done through macros defined in profiler.h. The macro must ensure (1) that the call is guarded against reentrance
and (2) that the call can be turned off at compile time using a -D_GLIBCXX_PROFILE_... compiler option.

19.6.2

How To Add A Diagnostic

Let’s say the diagnostic name is "magic".
If you need to instrument a header not already under include/profile/*, first edit the corresponding header under incl
ude/std/ and add a preprocessor directive such as the one in include/std/vector:
#ifdef _GLIBCXX_PROFILE
# include 
#endif

If the file you need to instrument is not yet under include/profile/, make a copy of the one in include/debug, or the
main implementation. You’ll need to include the main implementation and inherit the classes you want to instrument. Then define
the methods you want to instrument, define the instrumentation hooks and add calls to them. Look at include/profile/
vector for an example.
Add macros for the instrumentation hooks in include/profile/impl/profiler.h. Hook names must start with __pr
ofcxx_. Make sure they transform in no code with -D_NO_GLIBCXX_PROFILE_MAGIC. Make sure all calls to any method
in namespace __gnu_profile is protected against reentrance using macro _GLIBCXX_PROFILE_REENTRANCE_GUARD.
All names of methods in namespace __gnu_profile called from profiler.h must start with __trace_magic_.
Add the implementation of the diagnostic.
• Create new file include/profile/impl/profiler_magic.h.
• Define class __magic_info:public __object_info_base. This is the representation of a line in the object table.
The __merge method is used to aggregate information across all dynamic instances created at the same call context. The
__magnitude must return the estimation of the benefit as a number of small operations, e.g., number of words copied. The
__write method is used to produce the raw trace. The __advice method is used to produce the advice string.
• Define class __magic_stack_info:public __magic_info. This defines the content of a line in the stack table.
• Define class __trace_magic:public __trace_base<__magic_info, __magic_stack_info>. It defines
the content of the trace associated with this diagnostic.
Add initialization and reporting calls in include/profile/impl/profiler_trace.h. Use __trace_vector_to
_list as an example.
Add documentation in file doc/xml/manual/profile_mode.xml.

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Diagnostics

The table below presents all the diagnostics we intend to implement. Each diagnostic has a corresponding compile time switch D_GLIBCXX_PROFILE_. Groups of related diagnostics can be turned on with a single switch. For instance,
-D_GLIBCXX_PROFILE_LOCALITY is equivalent to -D_GLIBCXX_PROFILE_SOFTWARE_PREFETCH -D_GLIBCXX
_PROFILE_RBTREE_LOCALITY.
The benefit, cost, expected frequency and accuracy of each diagnostic was given a grade from 1 to 10, where 10 is highest. A
high benefit means that, if the diagnostic is accurate, the expected performance improvement is high. A high cost means that
turning this diagnostic on leads to high slowdown. A high frequency means that we expect this to occur relatively often. A high
accuracy means that the diagnostic is unlikely to be wrong. These grades are not perfect. They are just meant to guide users with
specific needs or time budgets.
Group
Flag
Benefit
CONTAINERS HASHTABLE_TOO_SMALL
10
HASHTABLE_TOO_LARGE
5
INEFFICIENT_HASH
7
VECTOR_TOO_SMALL
8
VECTOR_TOO_LARGE
5
VECTOR_TO_HASHTABLE
7
HASHTABLE_TO_VECTOR
7
VECTOR_TO_LIST
8
LIST_TO_VECTOR
10
ORDERED_TO_UNORDERED
10
ALGORITHMS SORT
7
LOCALITY
SOFTWARE_PREFETCH
8
RBTREE_LOCALITY
4
FALSE_SHARING
8

Cost
1
1
3
1
1
7
7
5
5

Freq.

Implemented
10
10
10
10
10
10
10
10
10

5

10

8
8
8
10

7
5
5
10

yes
yes
yes
yes
yes
no
no
yes
no
only
map/unordered_map
no
no
no
no

Table 19.2: Profile Diagnostics

19.7.1

Diagnostic Template

• Switch: _GLIBCXX_PROFILE_.
• Goal: What problem will it diagnose?
• Fundamentals:. What is the fundamental reason why this is a problem
• Sample runtime reduction: Percentage reduction in execution time. When reduction is more than a constant factor, describe
the reduction rate formula.
• Recommendation: What would the advise look like?
• To instrument: What stdlibc++ components need to be instrumented?
• Analysis: How do we decide when to issue the advice?
• Cost model: How do we measure benefits? Math goes here.
• Example:
program code
...
advice sample

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Containers

Switch: _GLIBCXX_PROFILE_CONTAINERS.
19.7.2.1

Hashtable Too Small

• Switch: _GLIBCXX_PROFILE_HASHTABLE_TOO_SMALL.
• Goal: Detect hashtables with many rehash operations, small construction size and large destruction size.
• Fundamentals: Rehash is very expensive. Read content, follow chains within bucket, evaluate hash function, place at new
location in different order.
• Sample runtime reduction: 36%. Code similar to example below.
• Recommendation: Set initial size to N at construction site S.
• To instrument: unordered_set, unordered_map constructor, destructor, rehash.
• Analysis: For each dynamic instance of unordered_[multi]set|map, record initial size and call context of the constructor. Record size increase, if any, after each relevant operation such as insert. Record the estimated rehash cost.
• Cost model: Number of individual rehash operations * cost per rehash.
• Example:
1 unordered_set us;
2 for (int k = 0; k < 1000000; ++k) {
3
us.insert(k);
4 }
foo.cc:1: advice: Changing initial unordered_set size from 10 to 1000000 saves 1025530
rehash operations.

19.7.2.2

←-

Hashtable Too Large

• Switch: _GLIBCXX_PROFILE_HASHTABLE_TOO_LARGE.
• Goal: Detect hashtables which are never filled up because fewer elements than reserved are ever inserted.
• Fundamentals: Save memory, which is good in itself and may also improve memory reference performance through fewer
cache and TLB misses.
• Sample runtime reduction: unknown.
• Recommendation: Set initial size to N at construction site S.
• To instrument: unordered_set, unordered_map constructor, destructor, rehash.
• Analysis: For each dynamic instance of unordered_[multi]set|map, record initial size and call context of the constructor, and correlate it with its size at destruction time.
• Cost model: Number of iteration operations + memory saved.
• Example:
1 vector> v(100000, unordered_set(100)) ;
2 for (int k = 0; k < 100000; ++k) {
3
for (int j = 0; j < 10; ++j) {
4
v[k].insert(k + j);
5 }
6 }
foo.cc:1: advice: Changing initial unordered_set size from 100 to 10 saves N
bytes of memory and M iteration steps.

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Inefficient Hash

• Switch: _GLIBCXX_PROFILE_INEFFICIENT_HASH.
• Goal: Detect hashtables with polarized distribution.
• Fundamentals: A non-uniform distribution may lead to long chains, thus possibly increasing complexity by a factor up to the
number of elements.
• Sample runtime reduction: factor up to container size.
• Recommendation: Change hash function for container built at site S. Distribution score = N. Access score = S. Longest chain
= C, in bucket B.
• To instrument: unordered_set, unordered_map constructor, destructor, [], insert, iterator.
• Analysis: Count the exact number of link traversals.
• Cost model: Total number of links traversed.
• Example:
class dumb_hash {
public:
size_t operator() (int i) const { return 0; }
};
...
unordered_set hs;
...
for (int i = 0; i < COUNT; ++i) {
hs.find(i);
}

19.7.2.4

Vector Too Small

• Switch: _GLIBCXX_PROFILE_VECTOR_TOO_SMALL.
• Goal:Detect vectors with many resize operations, small construction size and large destruction size..
• Fundamentals:Resizing can be expensive. Copying large amounts of data takes time. Resizing many small vectors may have
allocation overhead and affect locality.
• Sample runtime reduction:%.
• Recommendation: Set initial size to N at construction site S.
• To instrument:vector.
• Analysis: For each dynamic instance of vector, record initial size and call context of the constructor. Record size increase,
if any, after each relevant operation such as push_back. Record the estimated resize cost.
• Cost model: Total number of words copied * time to copy a word.
• Example:
1 vector v;
2 for (int k = 0; k < 1000000; ++k) {
3
v.push_back(k);
4 }
foo.cc:1: advice: Changing initial vector size from 10 to 1000000 saves
copying 4000000 bytes and 20 memory allocations and deallocations.

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Vector Too Large

• Switch: _GLIBCXX_PROFILE_VECTOR_TOO_LARGE
• Goal:Detect vectors which are never filled up because fewer elements than reserved are ever inserted.
• Fundamentals:Save memory, which is good in itself and may also improve memory reference performance through fewer
cache and TLB misses.
• Sample runtime reduction:%.
• Recommendation: Set initial size to N at construction site S.
• To instrument:vector.
• Analysis: For each dynamic instance of vector, record initial size and call context of the constructor, and correlate it with its
size at destruction time.
• Cost model: Total amount of memory saved.
• Example:
1 vector> v(100000, vector(100)) ;
2 for (int k = 0; k < 100000; ++k) {
3
for (int j = 0; j < 10; ++j) {
4
v[k].insert(k + j);
5 }
6 }
foo.cc:1: advice: Changing initial vector size from 100 to 10 saves N
bytes of memory and may reduce the number of cache and TLB misses.

19.7.2.6

Vector to Hashtable

• Switch: _GLIBCXX_PROFILE_VECTOR_TO_HASHTABLE.
• Goal: Detect uses of vector that can be substituted with unordered_set to reduce execution time.
• Fundamentals: Linear search in a vector is very expensive, whereas searching in a hashtable is very quick.
• Sample runtime reduction:factor up to container size.
• Recommendation:Replace vector with unordered_set at site S.
• To instrument:vector operations and access methods.
• Analysis: For each dynamic instance of vector, record call context of the constructor. Issue the advice only if the only
methods called on this vector are push_back, insert and find.

• Cost model: Cost(vector::push_back) + cost(vector::insert) + cost(find, vector) - cost(unordered_set::insert) + cost(unordered_set::find)
• Example:
1 vector v;
...
2 for (int i = 0; i < 1000; ++i) {
3
find(v.begin(), v.end(), i);
4 }
foo.cc:1: advice: Changing "vector" to "unordered_set" will save about 500,000
comparisons.

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Hashtable to Vector

• Switch: _GLIBCXX_PROFILE_HASHTABLE_TO_VECTOR.
• Goal: Detect uses of unordered_set that can be substituted with vector to reduce execution time.
• Fundamentals: Hashtable iterator is slower than vector iterator.
• Sample runtime reduction:95%.
• Recommendation:Replace unordered_set with vector at site S.
• To instrument:unordered_set operations and access methods.
• Analysis: For each dynamic instance of unordered_set, record call context of the constructor. Issue the advice only if the
number of find, insert and [] operations on this unordered_set are small relative to the number of elements, and
methods begin or end are invoked (suggesting iteration).
• Cost model: Number of .
• Example:
1 unordered_set us;
...
2 int s = 0;
3 for (unordered_set::iterator it = us.begin(); it != us.end(); ++it) {
4
s += *it;
5 }
foo.cc:1: advice: Changing "unordered_set" to "vector" will save about N
indirections and may achieve better data locality.

19.7.2.8

Vector to List

• Switch: _GLIBCXX_PROFILE_VECTOR_TO_LIST.
• Goal: Detect cases where vector could be substituted with list for better performance.
• Fundamentals: Inserting in the middle of a vector is expensive compared to inserting in a list.
• Sample runtime reduction:factor up to container size.
• Recommendation:Replace vector with list at site S.
• To instrument:vector operations and access methods.
• Analysis: For each dynamic instance of vector, record the call context of the constructor. Record the overhead of each
insert operation based on current size and insert position. Report instance with high insertion overhead.
• Cost model: (Sum(cost(vector::method)) - Sum(cost(list::method)), for method in [push_back, insert, erase]) + (Cost(iterate
vector) - Cost(iterate list))
• Example:
1
2
3
4

vector v;
for (int i = 0; i < 10000; ++i) {
v.insert(v.begin(), i);
}

foo.cc:1: advice: Changing "vector" to "list" will save about 5,000,000
operations.

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List to Vector

• Switch: _GLIBCXX_PROFILE_LIST_TO_VECTOR.
• Goal: Detect cases where list could be substituted with vector for better performance.
• Fundamentals: Iterating through a vector is faster than through a list.
• Sample runtime reduction:64%.
• Recommendation:Replace list with vector at site S.
• To instrument:vector operations and access methods.
• Analysis: Issue the advice if there are no insert operations.
• Cost model: (Sum(cost(vector::method)) - Sum(cost(list::method)), for method in [push_back, insert, erase]) + (Cost(iterate
vector) - Cost(iterate list))
• Example:
1 list l;
...
2 int sum = 0;
3 for (list::iterator it = l.begin(); it != l.end(); ++it) {
4
sum += *it;
5 }
foo.cc:1: advice: Changing "list" to "vector" will save about 1000000 indirect
memory references.

19.7.2.10

List to Forward List (Slist)

• Switch: _GLIBCXX_PROFILE_LIST_TO_SLIST.
• Goal: Detect cases where list could be substituted with forward_list for better performance.
• Fundamentals: The memory footprint of a forward_list is smaller than that of a list. This has beneficial effects on memory
subsystem, e.g., fewer cache misses.
• Sample runtime reduction:40%. Note that the reduction is only noticeable if the size of the forward_list node is in fact larger
than that of the list node. For memory allocators with size classes, you will only notice an effect when the two node sizes
belong to different allocator size classes.
• Recommendation:Replace list with forward_list at site S.
• To instrument:list operations and iteration methods.
• Analysis: Issue the advice if there are no backwards traversals or insertion before a given node.
• Cost model: Always true.
• Example:
1 list l;
...
2 int sum = 0;
3 for (list::iterator it = l.begin(); it != l.end(); ++it) {
4
sum += *it;
5 }
foo.cc:1: advice: Change "list" to "forward_list".

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Ordered to Unordered Associative Container

• Switch: _GLIBCXX_PROFILE_ORDERED_TO_UNORDERED.
• Goal: Detect cases where ordered associative containers can be replaced with unordered ones.
• Fundamentals: Insert and search are quicker in a hashtable than in a red-black tree.
• Sample runtime reduction:52%.
• Recommendation: Replace set with unordered_set at site S.
• To instrument: set, multiset, map, multimap methods.
• Analysis: Issue the advice only if we are not using operator ++ on any iterator on a particular [multi]set|map.
• Cost model: (Sum(cost(hashtable::method)) - Sum(cost(rbtree::method)), for method in [insert, erase, find]) + (Cost(iterate
hashtable) - Cost(iterate rbtree))
• Example:
1
2
3
4
5
6
7
8

set s;
for (int i = 0; i < 100000; ++i) {
s.insert(i);
}
int sum = 0;
for (int i = 0; i < 100000; ++i) {
sum += *s.find(i);
}

19.7.3

Algorithms

Switch: _GLIBCXX_PROFILE_ALGORITHMS.
19.7.3.1

Sort Algorithm Performance

• Switch: _GLIBCXX_PROFILE_SORT.
• Goal: Give measure of sort algorithm performance based on actual input. For instance, advise Radix Sort over Quick Sort for
a particular call context.
• Fundamentals: See papers: A framework for adaptive algorithm selection in STAPL and Optimizing Sorting with Machine
Learning Algorithms.
• Sample runtime reduction:60%.
• Recommendation: Change sort algorithm at site S from X Sort to Y Sort.
• To instrument: sort algorithm.
• Analysis: Issue the advice if the cost model tells us that another sort algorithm would do better on this input. Requires us to
know what algorithm we are using in our sort implementation in release mode.
• Cost model: Runtime(algo) for algo in [radix, quick, merge, ...]
• Example:

19.7.4

Data Locality

Switch: _GLIBCXX_PROFILE_LOCALITY.

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Need Software Prefetch

• Switch: _GLIBCXX_PROFILE_SOFTWARE_PREFETCH.
• Goal: Discover sequences of indirect memory accesses that are not regular, thus cannot be predicted by hardware prefetchers.
• Fundamentals: Indirect references are hard to predict and are very expensive when they miss in caches.
• Sample runtime reduction:25%.
• Recommendation: Insert prefetch instruction.
• To instrument: Vector iterator and access operator [].
• Analysis: First, get cache line size and page size from system. Then record iterator dereference sequences for which the value
is a pointer. For each sequence within a container, issue a warning if successive pointer addresses are not within cache lines
and do not form a linear pattern (otherwise they may be prefetched by hardware). If they also step across page boundaries,
make the warning stronger.
The same analysis applies to containers other than vector. However, we cannot give the same advice for linked structures, such
as list, as there is no random access to the n-th element. The user may still be able to benefit from this information, for instance
by employing frays (user level light weight threads) to hide the latency of chasing pointers.
This analysis is a little oversimplified. A better cost model could be created by understanding the capability of the hardware
prefetcher. This model could be trained automatically by running a set of synthetic cases.
• Cost model: Total distance between pointer values of successive elements in vectors of pointers.
• Example:
1
2
3
4
5
6
7
8

int zero = 0;
vector v(10000000, &zero);
for (int k = 0; k < 10000000; ++k) {
v[random() % 10000000] = new int(k);
}
for (int j = 0; j < 10000000; ++j) {
count += (*v[j] == 0 ? 0 : 1);
}

foo.cc:7: advice: Insert prefetch instruction.

19.7.4.2

Linked Structure Locality

• Switch: _GLIBCXX_PROFILE_RBTREE_LOCALITY.
• Goal: Give measure of locality of objects stored in linked structures (lists, red-black trees and hashtables) with respect to their
actual traversal patterns.
• Fundamentals:Allocation can be tuned to a specific traversal pattern, to result in better data locality. See paper: Custom
Memory Allocation for Free by Jula and Rauchwerger.
• Sample runtime reduction:30%.
• Recommendation: High scatter score N for container built at site S. Consider changing allocation sequence or choosing a
structure conscious allocator.
• To instrument: Methods of all containers using linked structures.
• Analysis: First, get cache line size and page size from system. Then record the number of successive elements that are on
different line or page, for each traversal method such as find. Give advice only if the ratio between this number and the
number of total node hops is above a threshold.
• Cost model: Sum(same_cache_line(this,previous))

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• Example:
1
2
3
4
5
6
7
8
9
...

set s;
for (int i = 0; i < 10000000; ++i) {
s.insert(i);
}
set s1, s2;
for (int i = 0; i < 10000000; ++i) {
s1.insert(i);
s2.insert(i);
}

10
11
12
13
14
15

// Fast, better locality.
for (set::iterator it = s.begin(); it != s.end(); ++it) {
sum += *it;
}
// Slow, elements are further apart.
for (set::iterator it = s1.begin(); it != s1.end(); ++it) {
sum += *it;
}

foo.cc:5: advice: High scatter score NNN for set built here. Consider changing
the allocation sequence or switching to a structure conscious allocator.

19.7.5

Multithreaded Data Access

The diagnostics in this group are not meant to be implemented short term. They require compiler support to know when container
elements are written to. Instrumentation can only tell us when elements are referenced.
Switch: _GLIBCXX_PROFILE_MULTITHREADED.
19.7.5.1

Data Dependence Violations at Container Level

• Switch: _GLIBCXX_PROFILE_DDTEST.
• Goal: Detect container elements that are referenced from multiple threads in the parallel region or across parallel regions.
• Fundamentals: Sharing data between threads requires communication and perhaps locking, which may be expensive.
• Sample runtime reduction:?%.
• Recommendation: Change data distribution or parallel algorithm.
• To instrument: Container access methods and iterators.
• Analysis: Keep a shadow for each container. Record iterator dereferences and container member accesses. Issue advice
for elements referenced by multiple threads. See paper: The LRPD test: speculative run-time parallelization of loops with
privatization and reduction parallelization.
• Cost model: Number of accesses to elements referenced from multiple threads
• Example:

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False Sharing

• Switch: _GLIBCXX_PROFILE_FALSE_SHARING.
• Goal: Detect elements in the same container which share a cache line, are written by at least one thread, and accessed by
different threads.
• Fundamentals: Under these assumptions, cache protocols require communication to invalidate lines, which may be expensive.
• Sample runtime reduction:68%.
• Recommendation: Reorganize container or use padding to avoid false sharing.
• To instrument: Container access methods and iterators.
• Analysis: First, get the cache line size. For each shared container, record all the associated iterator dereferences and member
access methods with the thread id. Compare the address lists across threads to detect references in two different threads to the
same cache line. Issue a warning only if the ratio to total references is significant. Do the same for iterator dereference values
if they are pointers.
• Cost model: Number of accesses to same cache line from different threads.
• Example:
1
vector v(2, 0);
2 #pragma omp parallel for shared(v, SIZE) schedule(static, 1)
3
for (i = 0; i < SIZE; ++i) {
4
v[i % 2] += i;
5
}
OMP_NUM_THREADS=2 ./a.out
foo.cc:1: advice: Change container structure or padding to avoid false
sharing in multithreaded access at foo.cc:4. Detected N shared cache lines.

19.7.6

Statistics

Switch: _GLIBCXX_PROFILE_STATISTICS.
In some cases the cost model may not tell us anything because the costs appear to offset the benefits. Consider the choice between
a vector and a list. When there are both inserts and iteration, an automatic advice may not be issued. However, the programmer
may still be able to make use of this information in a different way.
This diagnostic will not issue any advice, but it will print statistics for each container construction site. The statistics will contain
the cost of each operation actually performed on the container.

19.8

Bibliography
[54] Lixia LiuSilvius Rus, Copyright © 2009 , Proceedings of the 2009 International Symposium on Code Generation and Optimization .

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Chapter 20

The mt_allocator
20.1

Intro

The mt allocator [hereinafter referred to simply as "the allocator"] is a fixed size (power of two) allocator that was initially
developed specifically to suit the needs of multi threaded applications [hereinafter referred to as an MT application]. Over
time the allocator has evolved and been improved in many ways, in particular it now also does a good job in single threaded
applications [hereinafter referred to as a ST application]. (Note: In this document, when referring to single threaded applications
this also includes applications that are compiled with gcc without thread support enabled. This is accomplished using ifdef’s on
__GTHREADS). This allocator is tunable, very flexible, and capable of high-performance.
The aim of this document is to describe - from an application point of view - the "inner workings" of the allocator.

20.2

Design Issues

20.2.1

Overview

There are three general components to the allocator: a datum describing the characteristics of the memory pool, a policy class
containing this pool that links instantiation types to common or individual pools, and a class inheriting from the policy class that
is the actual allocator.
The datum describing pools characteristics is
template
class __pool

This class is parametrized on thread support, and is explicitly specialized for both multiple threads (with bool==true) and
single threads (via bool==false.) It is possible to use a custom pool datum instead of the default class that is provided.
There are two distinct policy classes, each of which can be used with either type of underlying pool datum.
template
struct __common_pool_policy
template
struct __per_type_pool_policy

The first policy, __common_pool_policy, implements a common pool. This means that allocators that are instantiated with
different types, say char and long will both use the same pool. This is the default policy.
The second policy, __per_type_pool_policy, implements a separate pool for each instantiating type. Thus, char and
long will use separate pools. This allows per-type tuning, for instance.
Putting this all together, the actual allocator class is

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template
class __mt_alloc : public __mt_alloc_base<_Tp>, _Poolp

This class has the interface required for standard library allocator classes, namely member functions allocate and dealloc
ate, plus others.

20.3

Implementation

20.3.1

Tunable Parameters

Certain allocation parameters can be modified, or tuned. There exists a nested struct __pool_base::_Tune that contains
all these parameters, which include settings for
• Alignment
• Maximum bytes before calling ::operator new directly
• Minimum bytes
• Size of underlying global allocations
• Maximum number of supported threads
• Migration of deallocations to the global free list
• Shunt for global new and delete
Adjusting parameters for a given instance of an allocator can only happen before any allocations take place, when the allocator
itself is initialized. For instance:
#include 
struct pod
{
int i;
int j;
};
int main()
{
typedef pod value_type;
typedef __gnu_cxx::__mt_alloc allocator_type;
typedef __gnu_cxx::__pool_base::_Tune tune_type;
tune_type t_default;
tune_type t_opt(16, 5120, 32, 5120, 20, 10, false);
tune_type t_single(16, 5120, 32, 5120, 1, 10, false);
tune_type t;
t = allocator_type::_M_get_options();
allocator_type::_M_set_options(t_opt);
t = allocator_type::_M_get_options();
allocator_type a;
allocator_type::pointer p1 = a.allocate(128);
allocator_type::pointer p2 = a.allocate(5128);
a.deallocate(p1, 128);
a.deallocate(p2, 5128);

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return 0;
}

20.3.2

Initialization

The static variables (pointers to freelists, tuning parameters etc) are initialized as above, or are set to the global defaults.
The very first allocate() call will always call the _S_initialize_once() function. In order to make sure that this function is called
exactly once we make use of a __gthread_once call in MT applications and check a static bool (_S_init) in ST applications.
The _S_initialize() function: - If the GLIBCXX_FORCE_NEW environment variable is set, it sets the bool _S_force_new to
true and then returns. This will cause subsequent calls to allocate() to return memory directly from a new() call, and deallocate
will only do a delete() call.
- If the GLIBCXX_FORCE_NEW environment variable is not set, both ST and MT applications will: - Calculate the number of
bins needed. A bin is a specific power of two size of bytes. I.e., by default the allocator will deal with requests of up to 128 bytes
(or whatever the value of _S_max_bytes is when _S_init() is called). This means that there will be bins of the following sizes (in
bytes): 1, 2, 4, 8, 16, 32, 64, 128. - Create the _S_binmap array. All requests are rounded up to the next "large enough" bin. I.e.,
a request for 29 bytes will cause a block from the "32 byte bin" to be returned to the application. The purpose of _S_binmap is
to speed up the process of finding out which bin to use. I.e., the value of _S_binmap[ 29 ] is initialized to 5 (bin 5 = 32 bytes).
- Create the _S_bin array. This array consists of bin_records. There will be as many bin_records in this array as the number
of bins that we calculated earlier. I.e., if _S_max_bytes = 128 there will be 8 entries. Each bin_record is then initialized: bin_record->first = An array of pointers to block_records. There will be as many block_records pointers as there are maximum
number of threads (in a ST application there is only 1 thread, in a MT application there are _S_max_threads). This holds the
pointer to the first free block for each thread in this bin. I.e., if we would like to know where the first free block of size 32 for
thread number 3 is we would look this up by: _S_bin[ 5 ].first[ 3 ] The above created block_record pointers members are now
initialized to their initial values. I.e. _S_bin[ n ].first[ n ] = NULL;
- Additionally a MT application will: - Create a list of free thread id’s. The pointer to the first entry is stored in _S_thread_freelist_first.
The reason for this approach is that the __gthread_self() call will not return a value that corresponds to the maximum number
of threads allowed but rather a process id number or something else. So what we do is that we create a list of thread_records.
This list is _S_max_threads long and each entry holds a size_t thread_id which is initialized to 1, 2, 3, 4, 5 and so on up to
_S_max_threads. Each time a thread calls allocate() or deallocate() we call _S_get_thread_id() which looks at the value of
_S_thread_key which is a thread local storage pointer. If this is NULL we know that this is a newly created thread and we
pop the first entry from this list and saves the pointer to this record in the _S_thread_key variable. The next time we will get
the pointer to the thread_record back and we use the thread_record->thread_id as identification. I.e., the first thread that calls
allocate will get the first record in this list and thus be thread number 1 and will then find the pointer to its first free 32 byte block
in _S_bin[ 5 ].first[ 1 ] When we create the _S_thread_key we also define a destructor (_S_thread_key_destr) which means that
when the thread dies, this thread_record is returned to the front of this list and the thread id can then be reused if a new thread is
created. This list is protected by a mutex (_S_thread_freelist_mutex) which is only locked when records are removed or added
to the list.
- Initialize the free and used counters of each bin_record: - bin_record->free = An array of size_t. This keeps track of the number
of blocks on a specific thread’s freelist in each bin. I.e., if a thread has 12 32-byte blocks on it’s freelists and allocates one of
these, this counter would be decreased to 11. - bin_record->used = An array of size_t. This keeps track of the number of blocks
currently in use of this size by this thread. I.e., if a thread has made 678 requests (and no deallocations...) of 32-byte blocks this
counter will read 678. The above created arrays are now initialized with their initial values. I.e. _S_bin[ n ].free[ n ] = 0;
- Initialize the mutex of each bin_record: The bin_record->mutex is used to protect the global freelist. This concept of a global
freelist is explained in more detail in the section "A multi threaded example", but basically this mutex is locked whenever a block
of memory is retrieved or returned to the global freelist for this specific bin. This only occurs when a number of blocks are
grabbed from the global list to a thread specific list or when a thread decides to return some blocks to the global freelist.

20.3.3

Deallocation Notes

Notes about deallocation. This allocator does not explicitly release memory. Because of this, memory debugging programs like
valgrind or purify may notice leaks: sorry about this inconvenience. Operating systems will reclaim allocated memory at program

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termination anyway. If sidestepping this kind of noise is desired, there are three options: use an allocator, like new_allocator
that releases memory while debugging, use GLIBCXX_FORCE_NEW to bypass the allocator’s internal pools, or use a custom
pool datum that releases resources on destruction.
On systems with the function __cxa_atexit, the allocator can be forced to free all memory allocated before program termination with the member function __pool_type::_M_destroy. However, because this member function relies on the
precise and exactly-conforming ordering of static destructors, including those of a static local __pool object, it should not be
used, ever, on systems that don’t have the necessary underlying support. In addition, in practice, forcing deallocation can be
tricky, as it requires the __pool object to be fully-constructed before the object that uses it is fully constructed. For most (but
not all) STL containers, this works, as an instance of the allocator is constructed as part of a container’s constructor. However,
this assumption is implementation-specific, and subject to change. For an example of a pool that frees memory, see the following
example.

20.4

Single Thread Example

Let’s start by describing how the data on a freelist is laid out in memory. This is the first two blocks in freelist for thread id 3 in
bin 3 (8 bytes):
+----------------+
| next* ---------|--+
|
| |
|
| |
|
| |
+----------------+ |
| thread_id = 3 | |
|
| |
|
| |
|
| |
+----------------+ |
| DATA
| |
|
| |
|
| |
|
| |
|
| |
|
| |
|
| |
|
| |
+----------------+ |
+----------------+ |
| next*
|<-+
|
|
|
|
|
|
+----------------+
| thread_id = 3 |
|
|
|
|
|
|
+----------------+
| DATA
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
+----------------+

(_S_bin[ 3 ].first[ 3 ] points here)

(A pointer to here is what is returned to the
the application when needed)

(If next == NULL it’s the last one on the list)

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With this in mind we simplify things a bit for a while and say that there is only one thread (a ST application). In this case all
operations are made to what is referred to as the global pool - thread id 0 (No thread may be assigned this id since they span from
1 to _S_max_threads in a MT application).
When the application requests memory (calling allocate()) we first look at the requested size and if this is > _S_max_bytes we
call new() directly and return.
If the requested size is within limits we start by finding out from which bin we should serve this request by looking in _S_binmap.
A quick look at _S_bin[ bin ].first[ 0 ] tells us if there are any blocks of this size on the freelist (0). If this is not NULL - fine,
just remove the block that _S_bin[ bin ].first[ 0 ] points to from the list, update _S_bin[ bin ].first[ 0 ] and return a pointer to that
blocks data.
If the freelist is empty (the pointer is NULL) we must get memory from the system and build us a freelist within this memory.
All requests for new memory is made in chunks of _S_chunk_size. Knowing the size of a block_record and the bytes that this
bin stores we then calculate how many blocks we can create within this chunk, build the list, remove the first block, update the
pointer (_S_bin[ bin ].first[ 0 ]) and return a pointer to that blocks data.
Deallocation is equally simple; the pointer is casted back to a block_record pointer, lookup which bin to use based on the size,
add the block to the front of the global freelist and update the pointer as needed (_S_bin[ bin ].first[ 0 ]).
The decision to add deallocated blocks to the front of the freelist was made after a set of performance measurements that showed
that this is roughly 10% faster than maintaining a set of "last pointers" as well.

20.5

Multiple Thread Example

In the ST example we never used the thread_id variable present in each block. Let’s start by explaining the purpose of this in a
MT application.
The concept of "ownership" was introduced since many MT applications allocate and deallocate memory to shared containers
from different threads (such as a cache shared amongst all threads). This introduces a problem if the allocator only returns
memory to the current threads freelist (I.e., there might be one thread doing all the allocation and thus obtaining ever more
memory from the system and another thread that is getting a longer and longer freelist - this will in the end consume all available
memory).
Each time a block is moved from the global list (where ownership is irrelevant), to a threads freelist (or when a new freelist is
built from a chunk directly onto a threads freelist or when a deallocation occurs on a block which was not allocated by the same
thread id as the one doing the deallocation) the thread id is set to the current one.
What’s the use? Well, when a deallocation occurs we can now look at the thread id and find out if it was allocated by another
thread id and decrease the used counter of that thread instead, thus keeping the free and used counters correct. And keeping the
free and used counters corrects is very important since the relationship between these two variables decides if memory should be
returned to the global pool or not when a deallocation occurs.
When the application requests memory (calling allocate()) we first look at the requested size and if this is >_S_max_bytes we
call new() directly and return.
If the requested size is within limits we start by finding out from which bin we should serve this request by looking in _S_binmap.
A call to _S_get_thread_id() returns the thread id for the calling thread (and if no value has been set in _S_thread_key, a new id
is assigned and returned).
A quick look at _S_bin[ bin ].first[ thread_id ] tells us if there are any blocks of this size on the current threads freelist. If this
is not NULL - fine, just remove the block that _S_bin[ bin ].first[ thread_id ] points to from the list, update _S_bin[ bin ].first[
thread_id ], update the free and used counters and return a pointer to that blocks data.
If the freelist is empty (the pointer is NULL) we start by looking at the global freelist (0). If there are blocks available on the
global freelist we lock this bins mutex and move up to block_count (the number of blocks of this bins size that will fit into a
_S_chunk_size) or until end of list - whatever comes first - to the current threads freelist and at the same time change the thread_id
ownership and update the counters and pointers. When the bins mutex has been unlocked, we remove the block that _S_bin[ bin
].first[ thread_id ] points to from the list, update _S_bin[ bin ].first[ thread_id ], update the free and used counters, and return a
pointer to that blocks data.

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The reason that the number of blocks moved to the current threads freelist is limited to block_count is to minimize the chance that
a subsequent deallocate() call will return the excess blocks to the global freelist (based on the _S_freelist_headroom calculation,
see below).
However if there isn’t any memory on the global pool we need to get memory from the system - this is done in exactly the same
way as in a single threaded application with one major difference; the list built in the newly allocated memory (of _S_chunk_size
size) is added to the current threads freelist instead of to the global.
The basic process of a deallocation call is simple: always add the block to the front of the current threads freelist and update the
counters and pointers (as described earlier with the specific check of ownership that causes the used counter of the thread that
originally allocated the block to be decreased instead of the current threads counter).
And here comes the free and used counters to service. Each time a deallocation() call is made, the length of the current threads
freelist is compared to the amount memory in use by this thread.
Let’s go back to the example of an application that has one thread that does all the allocations and one that deallocates. Both
these threads use say 516 32-byte blocks that was allocated during thread creation for example. Their used counters will both say
516 at this point. The allocation thread now grabs 1000 32-byte blocks and puts them in a shared container. The used counter for
this thread is now 1516.
The deallocation thread now deallocates 500 of these blocks. For each deallocation made the used counter of the allocating thread
is decreased and the freelist of the deallocation thread gets longer and longer. But the calculation made in deallocate() will limit
the length of the freelist in the deallocation thread to _S_freelist_headroom % of it’s used counter. In this case, when the freelist
(given that the _S_freelist_headroom is at it’s default value of 10%) exceeds 52 (516/10) blocks will be returned to the global
pool where the allocating thread may pick them up and reuse them.
In order to reduce lock contention (since this requires this bins mutex to be locked) this operation is also made in chunks of
blocks (just like when chunks of blocks are moved from the global freelist to a threads freelist mentioned above). The "formula"
used can probably be improved to further reduce the risk of blocks being "bounced back and forth" between freelists.

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Chapter 21

The bitmap_allocator
21.1

Design

As this name suggests, this allocator uses a bit-map to keep track of the used and unused memory locations for its book-keeping
purposes.
This allocator will make use of 1 single bit to keep track of whether it has been allocated or not. A bit 1 indicates free, while 0
indicates allocated. This has been done so that you can easily check a collection of bits for a free block. This kind of Bitmapped
strategy works best for single object allocations, and with the STL type parameterized allocators, we do not need to choose any
size for the block which will be represented by a single bit. This will be the size of the parameter around which the allocator has
been parameterized. Thus, close to optimal performance will result. Hence, this should be used for node based containers which
call the allocate function with an argument of 1.
The bitmapped allocator’s internal pool is exponentially growing. Meaning that internally, the blocks acquired from the Free List
Store will double every time the bitmapped allocator runs out of memory.
The macro __GTHREADS decides whether to use Mutex Protection around every allocation/deallocation. The state of the macro
is picked up automatically from the gthr abstraction layer.

21.2

Implementation

21.2.1

Free List Store

The Free List Store (referred to as FLS for the remaining part of this document) is the Global memory pool that is shared by all
instances of the bitmapped allocator instantiated for any type. This maintains a sorted order of all free memory blocks given back
to it by the bitmapped allocator, and is also responsible for giving memory to the bitmapped allocator when it asks for more.
Internally, there is a Free List threshold which indicates the Maximum number of free lists that the FLS can hold internally
(cache). Currently, this value is set at 64. So, if there are more than 64 free lists coming in, then some of them will be given back
to the OS using operator delete so that at any given time the Free List’s size does not exceed 64 entries. This is done because a
Binary Search is used to locate an entry in a free list when a request for memory comes along. Thus, the run-time complexity of
the search would go up given an increasing size, for 64 entries however, lg(64) == 6 comparisons are enough to locate the correct
free list if it exists.
Suppose the free list size has reached its threshold, then the largest block from among those in the list and the new block will be
selected and given back to the OS. This is done because it reduces external fragmentation, and allows the OS to use the larger
blocks later in an orderly fashion, possibly merging them later. Also, on some systems, large blocks are obtained via calls to
mmap, so giving them back to free system resources becomes most important.
The function _S_should_i_give decides the policy that determines whether the current block of memory should be given to the
allocator for the request that it has made. That’s because we may not always have exact fits for the memory size that the allocator
requests. We do this mainly to prevent external fragmentation at the cost of a little internal fragmentation. Now, the value of this

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internal fragmentation has to be decided by this function. I can see 3 possibilities right now. Please add more as and when you
find better strategies.
1. Equal size check. Return true only when the 2 blocks are of equal size.
2. Difference Threshold: Return true only when the _block_size is greater than or equal to the _required_size, and if the _BS
is > _RS by a difference of less than some THRESHOLD value, then return true, else return false.
3. Percentage Threshold. Return true only when the _block_size is greater than or equal to the _required_size, and if the _BS
is > _RS by a percentage of less than some THRESHOLD value, then return true, else return false.
Currently, (3) is being used with a value of 36% Maximum wastage per Super Block.

21.2.2

Super Block

A super block is the block of memory acquired from the FLS from which the bitmap allocator carves out memory for single objects and satisfies the user’s requests. These super blocks come in sizes that are powers of 2 and multiples of 32
(_Bits_Per_Block). Yes both at the same time! That’s because the next super block acquired will be 2 times the previous
one, and also all super blocks have to be multiples of the _Bits_Per_Block value.
How does it interact with the free list store?
The super block is contained in the FLS, and the FLS is responsible for getting / returning Super Bocks to and from the OS using
operator new as defined by the C++ standard.

21.2.3

Super Block Data Layout

Each Super Block will be of some size that is a multiple of the number of Bits Per Block. Typically, this value is chosen as
Bits_Per_Byte x sizeof(size_t). On an x86 system, this gives the figure 8 x 4 = 32. Thus, each Super Block will be of size 32
x Some_Value. This Some_Value is sizeof(value_type). For now, let it be called ’K’. Thus, finally, Super Block size is 32 x K
bytes.
This value of 32 has been chosen because each size_t has 32-bits and Maximum use of these can be made with such a figure.
Consider a block of size 64 ints. In memory, it would look like this: (assume a 32-bit system where, size_t is a 32-bit entity).
268

0

4294967295

4294967295

Data -> Space for 64
ints

Table 21.1: Bitmap Allocator Memory Map
The first Column(268) represents the size of the Block in bytes as seen by the Bitmap Allocator. Internally, a global free list is
used to keep track of the free blocks used and given back by the bitmap allocator. It is this Free List Store that is responsible for
writing and managing this information. Actually the number of bytes allocated in this case would be: 4 + 4 + (4x2) + (64x4) =
272 bytes, but the first 4 bytes are an addition by the Free List Store, so the Bitmap Allocator sees only 268 bytes. These first 4
bytes about which the bitmapped allocator is not aware hold the value 268.
What do the remaining values represent?
The 2nd 4 in the expression is the sizeof(size_t) because the Bitmapped Allocator maintains a used count for each Super Block,
which is initially set to 0 (as indicated in the diagram). This is incremented every time a block is removed from this super block
(allocated), and decremented whenever it is given back. So, when the used count falls to 0, the whole super block will be given
back to the Free List Store.

The value 4294967295 represents the integer corresponding to the bit representation of all bits set: 1111111111111111111111111111111
The 3rd 4x2 is size of the bitmap itself, which is the size of 32-bits x 2, which is 8-bytes, or 2 x sizeof(size_t).

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Maximum Wasted Percentage

This has nothing to do with the algorithm per-se, only with some vales that must be chosen correctly to ensure that the allocator
performs well in a real word scenario, and maintains a good balance between the memory consumption and the allocation/deallocation speed.
The formula for calculating the maximum wastage as a percentage:
(32 x k + 1) / (2 x (32 x k + 1 + 32 x c)) x 100.
where k is the constant overhead per node (e.g., for list, it is 8 bytes, and for map it is 12 bytes) and c is the size of the base
type on which the map/list is instantiated. Thus, suppose the type1 is int and type2 is double, they are related by the relation
sizeof(double) == 2*sizeof(int). Thus, all types must have this double size relation for this formula to work properly.
Plugging-in: For List: k = 8 and c = 4 (int and double), we get: 33.376%
For map/multimap: k = 12, and c = 4 (int and double), we get: 37.524%
Thus, knowing these values, and based on the sizeof(value_type), we may create a function that returns the Max_Wastage_Percentage
for us to use.

21.2.5 allocate
The allocate function is specialized for single object allocation ONLY. Thus, ONLY if n == 1, will the bitmap_allocator’s
specialized algorithm be used. Otherwise, the request is satisfied directly by calling operator new.
Suppose n == 1, then the allocator does the following:
1. Checks to see whether a free block exists somewhere in a region of memory close to the last satisfied request. If so, then
that block is marked as allocated in the bit map and given to the user. If not, then (2) is executed.
2. Is there a free block anywhere after the current block right up to the end of the memory that we have? If so, that block is
found, and the same procedure is applied as above, and returned to the user. If not, then (3) is executed.
3. Is there any block in whatever region of memory that we own free? This is done by checking
• The use count for each super block, and if that fails then
• The individual bit-maps for each super block.
Note: Here we are never touching any of the memory that the user will be given, and we are confining all memory accesses
to a small region of memory! This helps reduce cache misses. If this succeeds then we apply the same procedure on that
bit-map as (1), and return that block of memory to the user. However, if this process fails, then we resort to (4).
4. This process involves Refilling the internal exponentially growing memory pool. The said effect is achieved by calling
_S_refill_pool which does the following:
• Gets more memory from the Global Free List of the Required size.
• Adjusts the size for the next call to itself.
• Writes the appropriate headers in the bit-maps.
• Sets the use count for that super-block just allocated to 0 (zero).
• All of the above accounts to maintaining the basic invariant for the allocator. If the invariant is maintained, we are sure
that all is well. Now, the same process is applied on the newly acquired free blocks, which are dispatched accordingly.
Thus, you can clearly see that the allocate function is nothing but a combination of the next-fit and first-fit algorithm optimized
ONLY for single object allocations.

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21.2.6 deallocate
The deallocate function again is specialized for single objects ONLY. For all n belonging to > 1, the operator delete is called
without further ado, and the deallocate function returns.
However for n == 1, a series of steps are performed:
1. We first need to locate that super-block which holds the memory location given to us by the user. For that purpose, we
maintain a static variable _S_last_dealloc_index, which holds the index into the vector of block pairs which indicates the
index of the last super-block from which memory was freed. We use this strategy in the hope that the user will deallocate
memory in a region close to what he/she deallocated the last time around. If the check for belongs_to succeeds, then we
determine the bit-map for the given pointer, and locate the index into that bit-map, and mark that bit as free by setting it.
2. If the _S_last_dealloc_index does not point to the memory block that we’re looking for, then we do a linear search on
the block stored in the vector of Block Pairs. This vector in code is called _S_mem_blocks. When the corresponding
super-block is found, we apply the same procedure as we did for (1) to mark the block as free in the bit-map.
Now, whenever a block is freed, the use count of that particular super block goes down by 1. When this use count hits 0, we
remove that super block from the list of all valid super blocks stored in the vector. While doing this, we also make sure that the
basic invariant is maintained by making sure that _S_last_request and _S_last_dealloc_index point to valid locations within the
vector.

21.2.7

Questions

21.2.7.1

1

Q1) The "Data Layout" section is cryptic. I have no idea of what you are trying to say. Layout of what? The free-list? Each
bitmap? The Super Block?
The layout of a Super Block of a given size. In the example, a super block of size 32 x 1 is taken. The general formula for
calculating the size of a super block is 32 x sizeof(value_type) x 2ˆn, where n ranges from 0 to 32 for 32-bit systems.
21.2.7.2

2

And since I just mentioned the term `each bitmap’, what in the world is meant by it? What does each bitmap manage? How does
it relate to the super block? Is the Super Block a bitmap as well?
Each bitmap is part of a Super Block which is made up of 3 parts as I have mentioned earlier. Re-iterating, 1. The use count, 2.
The bit-map for that Super Block. 3. The actual memory that will be eventually given to the user. Each bitmap is a multiple of 32
in size. If there are 32 x (2ˆ3) blocks of single objects to be given, there will be ’32 x (2ˆ3)’ bits present. Each 32 bits managing
the allocated / free status for 32 blocks. Since each size_t contains 32-bits, one size_t can manage up to 32 blocks’ status. Each
bit-map is made up of a number of size_t, whose exact number for a super-block of a given size I have just mentioned.
21.2.7.3

3

How do the allocate and deallocate functions work in regard to bitmaps?
The allocate and deallocate functions manipulate the bitmaps and have nothing to do with the memory that is given to the user.
As I have earlier mentioned, a 1 in the bitmap’s bit field indicates free, while a 0 indicates allocated. This lets us check 32 bits
at a time to check whether there is at lease one free block in those 32 blocks by testing for equality with (0). Now, the allocate
function will given a memory block find the corresponding bit in the bitmap, and will reset it (i.e., make it re-set (0)). And when
the deallocate function is called, it will again set that bit after locating it to indicate that that particular block corresponding to
this bit in the bit-map is not being used by anyone, and may be used to satisfy future requests.

e.g.: Consider a bit-map of 64-bits as represented below: 1111111111111111111111111111111111111111111111111111111111111111
Now, when the first request for allocation of a single object comes along, the first block in address order is returned. And since
the bit-maps in the reverse order to that of the address order, the last bit (LSB if the bit-map is considered as a binary word of
64-bits) is re-set to 0.
The bit-map now looks like this: 1111111111111111111111111111111111111111111111111111111111111110

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Locality

Another issue would be whether to keep the all bitmaps in a separate area in memory, or to keep them near the actual blocks that
will be given out or allocated for the client. After some testing, I’ve decided to keep these bitmaps close to the actual blocks.
This will help in 2 ways.
1. Constant time access for the bitmap themselves, since no kind of look up will be needed to find the correct bitmap list or
its equivalent.
2. And also this would preserve the cache as far as possible.
So in effect, this kind of an allocator might prove beneficial from a purely cache point of view. But this allocator has been made
to try and roll out the defects of the node_allocator, wherein the nodes get skewed about in memory, if they are not returned in
the exact reverse order or in the same order in which they were allocated. Also, the new_allocator’s book keeping overhead is too
much for small objects and single object allocations, though it preserves the locality of blocks very well when they are returned
back to the allocator.

21.2.9

Overhead and Grow Policy

Expected overhead per block would be 1 bit in memory. Also, once the address of the free list has been found, the cost for
allocation/deallocation would be negligible, and is supposed to be constant time. For these very reasons, it is very important to
minimize the linear time costs, which include finding a free list with a free block while allocating, and finding the corresponding
free list for a block while deallocating. Therefore, I have decided that the growth of the internal pool for this allocator will
be exponential as compared to linear for node_allocator. There, linear time works well, because we are mainly concerned
with speed of allocation/deallocation and memory consumption, whereas here, the allocation/deallocation part does have some
linear/logarithmic complexity components in it. Thus, to try and minimize them would be a good thing to do at the cost of a little
bit of memory.
Another thing to be noted is the pool size will double every time the internal pool gets exhausted, and all the free blocks have
been given away. The initial size of the pool would be sizeof(size_t) x 8 which is the number of bits in an integer, which can fit
exactly in a CPU register. Hence, the term given is exponential growth of the internal pool.

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Chapter 22

Policy-Based Data Structures
22.1

Intro

This is a library of policy-based elementary data structures: associative containers and priority queues. It is designed for highperformance, flexibility, semantic safety, and conformance to the corresponding containers in std and std::tr1 (except for
some points where it differs by design).

22.1.1

Performance Issues

An attempt is made to categorize the wide variety of possible container designs in terms of performance-impacting factors. These
performance factors are translated into design policies and incorporated into container design.
There is tension between unravelling factors into a coherent set of policies. Every attempt is made to make a minimal set of
factors. However, in many cases multiple factors make for long template names. Every attempt is made to alias and use typedefs
in the source files, but the generated names for external symbols can be large for binary files or debuggers.
In many cases, the longer names allow capabilities and behaviours controlled by macros to also be unamibiguously emitted as
distinct generated names.
Specific issues found while unraveling performance factors in the design of associative containers and priority queues follow.
22.1.1.1

Associative

Associative containers depend on their composite policies to a very large extent. Implicitly hard-wiring policies can hamper
their performance and limit their functionality. An efficient hash-based container, for example, requires policies for testing key
equivalence, hashing keys, translating hash values into positions within the hash table, and determining when and how to resize
the table internally. A tree-based container can efficiently support order statistics, i.e. the ability to query what is the order of
each key within the sequence of keys in the container, but only if the container is supplied with a policy to internally update
meta-data. There are many other such examples.
Ideally, all associative containers would share the same interface. Unfortunately, underlying data structures and mapping semantics differentiate between different containers. For example, suppose one writes a generic function manipulating an associative
container.
template
void
some_op_sequence(Cntnr& r_cnt)
{
...
}

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Given this, then what can one assume about the instantiating container? The answer varies according to its underlying data
structure. If the underlying data structure of Cntnr is based on a tree or trie, then the order of elements is well defined;
otherwise, it is not, in general. If the underlying data structure of Cntnr is based on a collision-chaining hash table, then
modifying r_Cntnr will not invalidate its iterators’ order; if the underlying data structure is a probing hash table, then this is
not the case. If the underlying data structure is based on a tree or trie, then a reference to the container can efficiently be split;
otherwise, it cannot, in general. If the underlying data structure is a red-black tree, then splitting a reference to the container is
exception-free; if it is an ordered-vector tree, exceptions can be thrown.
22.1.1.2

Priority Que

Priority queues are useful when one needs to efficiently access a minimum (or maximum) value as the set of values changes.
Most useful data structures for priority queues have a relatively simple structure, as they are geared toward relatively simple
requirements. Unfortunately, these structures do not support access to an arbitrary value, which turns out to be necessary in many
algorithms. Say, decreasing an arbitrary value in a graph algorithm. Therefore, some extra mechanism is necessary and must
be invented for accessing arbitrary values. There are at least two alternatives: embedding an associative container in a priority
queue, or allowing cross-referencing through iterators. The first solution adds significant overhead; the second solution requires
a precise definition of iterator invalidation. Which is the next point...
Priority queues, like hash-based containers, store values in an order that is meaningless and undefined externally. For example,
a push operation can internally reorganize the values. Because of this characteristic, describing a priority queues’ iterator is
difficult: on one hand, the values to which iterators point can remain valid, but on the other, the logical order of iterators can
change unpredictably.
Roughly speaking, any element that is both inserted to a priority queue (e.g. through push) and removed from it (e.g., through
pop), incurs a logarithmic overhead (in the amortized sense). Different underlying data structures place the actual cost differently: some are optimized for amortized complexity, whereas others guarantee that specific operations only have a constant cost.
One underlying data structure might be chosen if modifying a value is frequent (Dijkstra’s shortest-path algorithm), whereas a
different one might be chosen otherwise. Unfortunately, an array-based binary heap - an underlying data structure that optimizes
(in the amortized sense) push and pop operations, differs from the others in terms of its invalidation guarantees. Other design
decisions also impact the cost and placement of the overhead, at the expense of more difference in the kinds of operations that the
underlying data structure can support. These differences pose a challenge when creating a uniform interface for priority queues.

22.1.2

Goals

Many fine associative-container libraries were already written, most notably, the C++ standard’s associative containers. Why
then write another library? This section shows some possible advantages of this library, when considering the challenges in the
introduction. Many of these points stem from the fact that the ISO C++ process introduced associative-containers in a two-step
process (first standardizing tree-based containers, only then adding hash-based containers, which are fundamentally different),
did not standardize priority queues as containers, and (in our opinion) overloads the iterator concept.
22.1.2.1
22.1.2.1.1

Associative
Policy Choices

Associative containers require a relatively large number of policies to function efficiently in various settings. In some cases
this is needed for making their common operations more efficient, and in other cases this allows them to support a larger set of
operations
1. Hash-based containers, for example, support look-up and insertion methods (find and insert). In order to locate
elements quickly, they are supplied a hash functor, which instruct how to transform a key object into some size type; a
hash functor might transform "hello" into 1123002298. A hash table, though, requires transforming each key object
into some size-type type in some specific domain; a hash table with a 128-long table might transform "hello" into
position 63. The policy by which the hash value is transformed into a position within the table can dramatically affect
performance. Hash-based containers also do not resize naturally (as opposed to tree-based containers, for example). The
appropriate resize policy is unfortunately intertwined with the policy that transforms hash value into a position within the
table.

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2. Tree-based containers, for example, also support look-up and insertion methods, and are primarily useful when maintaining
order between elements is important. In some cases, though, one can utilize their balancing algorithms for completely
different purposes.
Figure A shows a tree whose each node contains two entries: a floating-point key, and some size-type metadata (in bold
beneath it) that is the number of nodes in the sub-tree. (The root has key 0.99, and has 5 nodes (including itself) in its
sub-tree.) A container based on this data structure can obviously answer efficiently whether 0.3 is in the container object,
but it can also answer what is the order of 0.3 among all those in the container object: see [66].
As another example, Figure B shows a tree whose each node contains two entries: a half-open geometric line interval,
and a number metadata (in bold beneath it) that is the largest endpoint of all intervals in its sub-tree. (The root describes
the interval [20, 36), and the largest endpoint in its sub-tree is 99.) A container based on this data structure can
obviously answer efficiently whether [3, 41) is in the container object, but it can also answer efficiently whether the
container object has intervals that intersect [3, 41). These types of queries are very useful in geometric algorithms and
lease-management algorithms.
It is important to note, however, that as the trees are modified, their internal structure changes. To maintain these invariants,
one must supply some policy that is aware of these changes. Without this, it would be better to use a linked list (in itself
very efficient for these purposes).

Figure 22.1: Node Invariants

22.1.2.1.2

Underlying Data Structures

The standard C++ library contains associative containers based on red-black trees and collision-chaining hash tables. These are
very useful, but they are not ideal for all types of settings.
The figure below shows the different underlying data structures currently supported in this library.

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Figure 22.2: Underlying Associative Data Structures

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A shows a collision-chaining hash-table, B shows a probing hash-table, C shows a red-black tree, D shows a splay tree, E shows
a tree based on an ordered vector(implicit in the order of the elements), F shows a PATRICIA trie, and G shows a list-based
container with update policies.
Each of these data structures has some performance benefits, in terms of speed, size or both. For now, note that vector-based
trees and probing hash tables manipulate memory more efficiently than red-black trees and collision-chaining hash tables, and
that list-based associative containers are very useful for constructing "multimaps".
Now consider a function manipulating a generic associative container,
template
int
some_op_sequence(Cntnr &r_cnt)
{
...
}

Ideally, the underlying data structure of Cntnr would not affect what can be done with r_cnt. Unfortunately, this is not the
case.
For example, if Cntnr is std::map, then the function can use
std::for_each(r_cnt.find(foo), r_cnt.find(bar), foobar)

in order to apply foobar to all elements between foo and bar. If Cntnr is a hash-based container, then this call’s results are
undefined.
Also, if Cntnr is tree-based, the type and object of the comparison functor can be accessed. If Cntnr is hash based, these
queries are nonsensical.
There are various other differences based on the container’s underlying data structure. For one, they can be constructed by, and
queried for, different policies. Furthermore:
1. Containers based on C, D, E and F store elements in a meaningful order; the others store elements in a meaningless (and
probably time-varying) order. By implication, only containers based on C, D, E and F can support erase operations
taking an iterator and returning an iterator to the following element without performance loss.
2. Containers based on C, D, E, and F can be split and joined efficiently, while the others cannot. Containers based on C and
D, furthermore, can guarantee that this is exception-free; containers based on E cannot guarantee this.
3. Containers based on all but E can guarantee that erasing an element is exception free; containers based on E cannot
guarantee this. Containers based on all but B and E can guarantee that modifying an object of their type does not invalidate
iterators or references to their elements, while containers based on B and E cannot. Containers based on C, D, and E can
furthermore make a stronger guarantee, namely that modifying an object of their type does not affect the order of iterators.
A unified tag and traits system (as used for the C++ standard library iterators, for example) can ease generic manipulation of
associative containers based on different underlying data structures.
22.1.2.1.3

Iterators

Iterators are centric to the design of the standard library containers, because of the container/algorithm/iterator decomposition
that allows an algorithm to operate on a range through iterators of some sequence. Iterators, then, are useful because they allow
going over a specific sequence. The standard library also uses iterators for accessing a specific element: when an associative
container returns one through find. The standard library consistently uses the same types of iterators for both purposes: going
over a range, and accessing a specific found element. Before the introduction of hash-based containers to the standard library,
this made sense (with the exception of priority queues, which are discussed later).
Using the standard associative containers together with non-order-preserving associative containers (and also because of priorityqueues container), there is a possible need for different types of iterators for self-organizing containers: the iterator concept seems
overloaded to mean two different things (in some cases). .

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Using Point Iterators for Range Operations

Suppose cntnr is some associative container, and say c is an object of type cntnr. Then what will be the outcome of
std::for_each(c.find(1), c.find(5), foo);

If cntnr is a tree-based container object, then an in-order walk will apply foo to the relevant elements, as in the graphic below,
label A. If c is a hash-based container, then the order of elements between any two elements is undefined (and probably timevarying); there is no guarantee that the elements traversed will coincide with the logical elements between 1 and 5, as in label
B.

Figure 22.3: Range Iteration in Different Data Structures
In our opinion, this problem is not caused just because red-black trees are order preserving while collision-chaining hash tables
are (generally) not - it is more fundamental. Most of the standard’s containers order sequences in a well-defined manner that
is determined by their interface: calling insert on a tree-based container modifies its sequence in a predictable way, as does
calling push_back on a list or a vector. Conversely, collision-chaining hash tables, probing hash tables, priority queues, and
list-based containers (which are very useful for "multimaps") are self-organizing data structures; the effect of each operation
modifies their sequences in a manner that is (practically) determined by their implementation.
Consequently, applying an algorithm to a sequence obtained from most containers may or may not make sense, but applying it
to a sub-sequence of a self-organizing container does not.
22.1.2.1.3.2

Cost to Point Iterators to Enable Range Operations

Suppose c is some collision-chaining hash-based container object, and one calls
c.find(3)

Then what composes the returned iterator?
In the graphic below, label A shows the simplest (and most efficient) implementation of a collision-chaining hash table. The
little box marked point_iterator shows an object that contains a pointer to the element’s node. Note that this "iterator" has
no way to move to the next element ( it cannot support operator++). Conversely, the little box marked iterator stores
both a pointer to the element, as well as some other information (the bucket number of the element). the second iterator, then, is
"heavier" than the first one- it requires more time and space. If we were to use a different container to cross-reference into this
hash-table using these iterators - it would take much more space. As noted above, nothing much can be done by incrementing
these iterators, so why is this extra information needed?

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Alternatively, one might create a collision-chaining hash-table where the lists might be linked, forming a monolithic total-element
list, as in the graphic below, label B. Here the iterators are as light as can be, but the hash-table’s operations are more complicated.

Figure 22.4: Point Iteration in Hash Data Structures
It should be noted that containers based on collision-chaining hash-tables are not the only ones with this type of behavior; many
other self-organizing data structures display it as well.
22.1.2.1.3.3

Invalidation Guarantees

Consider the following snippet:
it = c.find(3);
c.erase(5);

Following the call to erase, what is the validity of it: can it be de-referenced? can it be incremented?
The answer depends on the underlying data structure of the container. The graphic below shows three cases: A1 and A2 show a
red-black tree; B1 and B2 show a probing hash-table; C1 and C2 show a collision-chaining hash table.

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Figure 22.5: Effect of erase in different underlying data structures
1. Erasing 5 from A1 yields A2. Clearly, an iterator to 3 can be de-referenced and incremented. The sequence of iterators
changed, but in a way that is well-defined by the interface.

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2. Erasing 5 from B1 yields B2. Clearly, an iterator to 3 is not valid at all - it cannot be de-referenced or incremented; the
order of iterators changed in a way that is (practically) determined by the implementation and not by the interface.
3. Erasing 5 from C1 yields C2. Here the situation is more complicated. On the one hand, there is no problem in dereferencing it. On the other hand, the order of iterators changed in a way that is (practically) determined by the implementation and not by the interface.
So in the standard library containers, it is not always possible to express whether it is valid or not. This is true also for insert.
Again, the iterator concept seems overloaded.
22.1.2.1.4

Functional

The design of the functional overlay to the underlying data structures differs slightly from some of the conventions used in the
C++ standard. A strict public interface of methods that comprise only operations which depend on the class’s internal structure;
other operations are best designed as external functions. (See [84]).With this rubric, the standard associative containers lack
some useful methods, and provide other methods which would be better removed.
22.1.2.1.4.1 erase

1. Order-preserving standard associative containers provide the method
iterator
erase(iterator it)

which takes an iterator, erases the corresponding element, and returns an iterator to the following element. Also standardd
hash-based associative containers provide this method. This seemingly increasesgenericity between associative containers,
since it is possible to use
typename C::iterator it = c.begin();
typename C::iterator e_it = c.end();
while(it != e_it)
it = pred(*it)? c.erase(it) : ++it;

in order to erase from a container object c all element which match a predicate pred. However, in a different sense
this actually decreases genericity: an integral implication of this method is that tree-based associative containers’ memory
use is linear in the total number of elements they store, while hash-based containers’ memory use is unbounded in the
total number of elements they store. Assume a hash-based container is allowed to decrease its size when an element
is erased. Then the elements might be rehashed, which means that there is no "next" element - it is simply undefined.
Consequently, it is possible to infer from the fact that the standard library’s hash-based containers provide this method
that they cannot downsize when elements are erased. As a consequence, different code is needed to manipulate different
containers, assuming that memory should be conserved. Therefor, this library’s non-order preserving associative containers
omit this method.
2. All associative containers include a conditional-erase method
template<
class Pred>
size_type
erase_if
(Pred pred)

which erases all elements matching a predicate. This is probably the only way to ensure linear-time multiple-item erase
which can actually downsize a container.
3. The standard associative containers provide methods for multiple-item erase of the form
size_type
erase(It b, It e)

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erasing a range of elements given by a pair of iterators. For tree-based or trie-based containers, this can implemented more
efficiently as a (small) sequence of split and join operations. For other, unordered, containers, this method isn’t much better
than an external loop. Moreover, if c is a hash-based container, then
c.erase(c.find(2), c.find(5))

is almost certain to do something different than erasing all elements whose keys are between 2 and 5, and is likely to
produce other undefined behavior.
22.1.2.1.4.2

split and join

It is well-known that tree-based and trie-based container objects can be efficiently split or joined (See [66]). Externally splitting
or joining trees is super-linear, and, furthermore, can throw exceptions. Split and join methods, consequently, seem good choices
for tree-based container methods, especially, since as noted just before, they are efficient replacements for erasing sub-sequences.
22.1.2.1.4.3

insert

The standard associative containers provide methods of the form
template
size_type
insert(It b, It e);

for inserting a range of elements given by a pair of iterators. At best, this can be implemented as an external loop, or, even more
efficiently, as a join operation (for the case of tree-based or trie-based containers). Moreover, these methods seem similar to
constructors taking a range given by a pair of iterators; the constructors, however, are transactional, whereas the insert methods
are not; this is possibly confusing.
22.1.2.1.4.4

operator== and operator<=

Associative containers are parametrized by policies allowing to test key equivalence: a hash-based container can do this through
its equivalence functor, and a tree-based container can do this through its comparison functor. In addition, some standard associative containers have global function operators, like operator== and operator<=, that allow comparing entire associative
containers.
In our opinion, these functions are better left out. To begin with, they do not significantly improve over an external loop.
More importantly, however, they are possibly misleading - operator==, for example, usually checks for equivalence, or
interchangeability, but the associative container cannot check for values’ equivalence, only keys’ equivalence; also, are two
containers considered equivalent if they store the same values in different order? this is an arbitrary decision.
22.1.2.2
22.1.2.2.1

Priority Queues
Policy Choices

Priority queues are containers that allow efficiently inserting values and accessing the maximal value (in the sense of the container’s comparison functor). Their interface supports push and pop. The standard container std::priorityqueue indeed
support these methods, but little else. For algorithmic and software-engineering purposes, other methods are needed:
1. Many graph algorithms (see [66]) require increasing a value in a priority queue (again, in the sense of the container’s
comparison functor), or joining two priority-queue objects.
2. The return type of priority_queue’s push method is a point-type iterator, which can be used for modifying or erasing
arbitrary values. For example:
priority_queue p;
priority_queue::point_iterator it = p.push(3);
p.modify(it, 4);

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These types of cross-referencing operations are necessary for making priority queues useful for different applications,
especially graph applications.
3. It is sometimes necessary to erase an arbitrary value in a priority queue. For example, consider the select function for
monitoring file descriptors:
int
select(int nfds, fd_set *readfds, fd_set *writefds, fd_set *errorfds,
struct timeval *timeout);

then, as the select documentation states:
“ The nfds argument specifies the range of file descriptors to be tested. The select() function tests file descriptors in the
range of 0 to nfds-1.”
It stands to reason, therefore, that we might wish to maintain a minimal value for nfds, and priority queues immediately
come to mind. Note, though, that when a socket is closed, the minimal file description might change; in the absence of an
efficient means to erase an arbitrary value from a priority queue, we might as well avoid its use altogether.
The standard containers typically support iterators. It is somewhat unusual for std::priority_queue to omit them
(See [83]). One might ask why do priority queues need to support iterators, since they are self-organizing containers with
a different purpose than abstracting sequences. There are several reasons:
(a) Iterators (even in self-organizing containers) are useful for many purposes: cross-referencing containers, serialization,
and debugging code that uses these containers.
(b) The standard library’s hash-based containers support iterators, even though they too are self-organizing containers
with a different purpose than abstracting sequences.
(c) In standard-library-like containers, it is natural to specify the interface of operations for modifying a value or erasing
a value (discussed previously) in terms of a iterators. It should be noted that the standard containers also use iterators
for accessing and manipulating a specific value. In hash-based containers, one checks the existence of a key by
comparing the iterator returned by find to the iterator returned by end, and not by comparing a pointer returned by
find to NULL.
22.1.2.2.2

Underlying Data Structures

There are three main implementations of priority queues: the first employs a binary heap, typically one which uses a sequence;
the second uses a tree (or forest of trees), which is typically less structured than an associative container’s tree; the third simply
uses an associative container. These are shown in the figure below with labels A1 and A2, B, and C.

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Figure 22.6: Underlying Priority Queue Data Structures
No single implementation can completely replace any of the others. Some have better push and pop amortized performance,
some have better bounded (worst case) response time than others, some optimize a single method at the expense of others, etc.
In general the "best" implementation is dictated by the specific problem.
As with associative containers, the more implementations co-exist, the more necessary a traits mechanism is for handling generic
containers safely and efficiently. This is especially important for priority queues, since the invalidation guarantees of one of the
most useful data structures - binary heaps - is markedly different than those of most of the others.
22.1.2.2.3

Binary Heaps

Binary heaps are one of the most useful underlying data structures for priority queues. They are very efficient in terms of memory
(since they don’t require per-value structure metadata), and have the best amortized push and pop performance for primitive
types like int.
The standard library’s priority_queue implements this data structure as an adapter over a sequence, typically std::
vector or std::deque, which correspond to labels A1 and A2 respectively in the graphic above.
This is indeed an elegant example of the adapter concept and the algorithm/container/iterator decomposition. (See [89]). There
are several reasons why a binary-heap priority queue may be better implemented as a container instead of a sequence adapter:
1. std::priority_queue cannot erase values from its adapted sequence (irrespective of the sequence type). This means
that the memory use of an std::priority_queue object is always proportional to the maximal number of values it
ever contained, and not to the number of values that it currently contains. (See performance/priority_queue_
text_pop_mem_usage.cc.) This implementation of binary heaps acts very differently than other underlying data
structures (See also pairing heaps).

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2. Some combinations of adapted sequences and value types are very inefficient or just don’t make sense. If one uses std:
:priority_queue > >, for example, then not only will each operation perform
a logarithmic number of std::string assignments, but, furthermore, any operation (including pop) can render the
container useless due to exceptions. Conversely, if one uses std::priority_queue > >,
then each operation uses incurs a logarithmic number of indirect accesses (through pointers) unnecessarily. It might be
better to let the container make a conservative deduction whether to use the structure in the graphic above, labels A1 or
A2.
3. There does not seem to be a systematic way to determine what exactly can be done with the priority queue.
(a) If p is a priority queue adapting an std::vector, then it is possible to iterate over all values by using &p.top()
and &p.top() + p.size(), but this will not work if p is adapting an std::deque; in any case, one cannot
use p.begin() and p.end(). If a different sequence is adapted, it is even more difficult to determine what can
be done.
(b) If p is a priority queue adapting an std::deque, then the reference return by
p.top()

will remain valid until it is popped, but if p adapts an std::vector, the next push will invalidate it. If a different
sequence is adapted, it is even more difficult to determine what can be done.
4. Sequence-based binary heaps can still implement linear-time erase and modify operations. This means that if one
needs to erase a small (say logarithmic) number of values, then one might still choose this underlying data structure. Using
std::priority_queue, however, this will generally change the order of growth of the entire sequence of operations.

22.2

Using

22.2.1

Prerequisites

The library contains only header files, and does not require any other libraries except the standard C++ library . All classes are
defined in namespace __gnu_pbds. The library internally uses macros beginning with PB_DS, but #undefs anything it #
defines (except for header guards). Compiling the library in an environment where macros beginning in PB_DS are defined,
may yield unpredictable results in compilation, execution, or both.
Further dependencies are necessary to create the visual output for the performance tests. To create these graphs, an additional
package is needed: pychart.

22.2.2

Organization

The various data structures are organized as follows.
• Branch-Based
– basic_branch is an abstract base class for branched-based associative-containers
– tree is a concrete base class for tree-based associative-containers
– trie is a concrete base class trie-based associative-containers
• Hash-Based
– basic_hash_table is an abstract base class for hash-based associative-containers
– cc_hash_table is a concrete collision-chaining hash-based associative-containers
– gp_hash_table is a concrete (general) probing hash-based associative-containers
• List-Based

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– list_update list-based update-policy associative container
• Heap-Based
– priority_queue A priority queue.
The hierarchy is composed naturally so that commonality is captured by base classes. Thus operator[] is defined at the base
of any hierarchy, since all derived containers support it. Conversely split is defined in basic_branch, since only tree-like
containers support it.
In addition, there are the following diagnostics classes, used to report errors specific to this library’s data structures.
std::exception

std::logic_error

__gnu_pbds::container_error

__gnu_pbds::insert_error

__gnu_pbds::join_error

__gnu_pbds::resize_error

Figure 22.7: Exception Hierarchy

22.2.3

Tutorial

22.2.3.1

Basic Use

For the most part, the policy-based containers containers in namespace __gnu_pbds have the same interface as the equivalent
containers in the standard C++ library, except for the names used for the container classes themselves. For example, this shows
basic operations on a collision-chaining hash-based container:
#include 
int main()
{
__gnu_pbds::cc_hash_table c;
c[2] = ’b’;
assert(c.find(1) == c.end());
};

The container is called __gnu_pbds::cc_hash_table instead of std::unordered_map, since “unordered map” does
not necessarily mean a hash-based map as implied by the C++ library (C++11 or TR1). For example, list-based associative
containers, which are very useful for the construction of "multimaps," are also unordered.
This snippet shows a red-black tree based container:
#include 
int main()
{
__gnu_pbds::tree c;
c[2] = ’b’;
assert(c.find(2) != c.end());
};

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The container is called tree instead of map since the underlying data structures are being named with specificity.
The member function naming convention is to strive to be the same as the equivalent member functions in other C++ standard
library containers. The familiar methods are unchanged: begin, end, size, empty, and clear.
This isn’t to say that things are exactly as one would expect, given the container requirments and interfaces in the C++ standard.
The names of containers’ policies and policy accessors are different then the usual. For example, if hash_type is some type of
hash-based container, then
hash_type::hash_fn

gives the type of its hash functor, and if obj is some hash-based container object, then
obj.get_hash_fn()

will return a reference to its hash-functor object.
Similarly, if tree_type is some type of tree-based container, then
tree_type::cmp_fn

gives the type of its comparison functor, and if obj is some tree-based container object, then
obj.get_cmp_fn()

will return a reference to its comparison-functor object.
It would be nice to give names consistent with those in the existing C++ standard (inclusive of TR1). Unfortunately, these
standard containers don’t consistently name types and methods. For example, std::tr1::unordered_map uses hasher for
the hash functor, but std::map uses key_compare for the comparison functor. Also, we could not find an accessor for std::
tr1::unordered_map’s hash functor, but std::map uses compare for accessing the comparison functor.
Instead, __gnu_pbds attempts to be internally consistent, and uses standard-derived terminology if possible.
Another source of difference is in scope: __gnu_pbds contains more types of associative containers than the standard C++
library, and more opportunities to configure these new containers, since different types of associative containers are useful in
different settings.
Namespace __gnu_pbds contains different classes for hash-based containers, tree-based containers, trie-based containers, and
list-based containers.
Since associative containers share parts of their interface, they are organized as a class hierarchy.
Each type or method is defined in the most-common ancestor in which it makes sense.
For example, all associative containers support iteration expressed in the following form:
const_iterator
begin() const;
iterator
begin();
const_iterator
end() const;
iterator
end();

But not all containers contain or use hash functors. Yet, both collision-chaining and (general) probing hash-based associative
containers have a hash functor, so basic_hash_table contains the interface:
const hash_fn&
get_hash_fn() const;
hash_fn&
get_hash_fn();

so all hash-based associative containers inherit the same hash-functor accessor methods.

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Configuring via Template Parameters

In general, each of this library’s containers is parametrized by more policies than those of the standard library. For example, the
standard hash-based container is parametrized as follows:
template
class unordered_map;

and so can be configured by key type, mapped type, a functor that translates keys to unsigned integral types, an equivalence
predicate, an allocator, and an indicator whether to store hash values with each entry. this library’s collision-chaining hash-based
container is parametrized as
template
class cc_hash_table;

and so can be configured by the first four types of std::tr1::unordered_map, then a policy for translating the key-hash
result into a position within the table, then a policy by which the table resizes, an indicator whether to store hash values with
each entry, and an allocator (which is typically the last template parameter in standard containers).
Nearly all policy parameters have default values, so this need not be considered for casual use. It is important to note, however,
that hash-based containers’ policies can dramatically alter their performance in different settings, and that tree-based containers’
policies can make them useful for other purposes than just look-up.
As opposed to associative containers, priority queues have relatively few configuration options. The priority queue is parametrized
as follows:
template
class priority_queue;

The Value_Type, Cmp_Fn, and Allocator parameters are the container’s value type, comparison-functor type, and allocator type, respectively; these are very similar to the standard’s priority queue. The Tag parameter is different: there are a number
of pre-defined tag types corresponding to binary heaps, binomial heaps, etc., and Tag should be instantiated by one of them.
Note that as opposed to the std::priority_queue, __gnu_pbds::priority_queue is not a sequence-adapter; it is
a regular container.
22.2.3.3

Querying Container Attributes

A containers underlying data structure affect their performance; Unfortunately, they can also affect their interface. When manipulating generically associative containers, it is often useful to be able to statically determine what they can support and what the
cannot.
Happily, the standard provides a good solution to a similar problem - that of the different behavior of iterators. If It is an iterator,
then
typename std::iterator_traits::iterator_category

is one of a small number of pre-defined tag classes, and
typename std::iterator_traits::value_type

is the value type to which the iterator "points".
Similarly, in this library, if C is a container, then container_traits is a trait class that stores information about the kind of
container that is implemented.
typename container_traits::container_category

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is one of a small number of predefined tag structures that uniquely identifies the type of underlying data structure.
In most cases, however, the exact underlying data structure is not really important, but what is important is one of its other
attributes: whether it guarantees storing elements by key order, for example. For this one can use
typename container_traits::order_preserving

Also,
typename container_traits::invalidation_guarantee

is the container’s invalidation guarantee. Invalidation guarantees are especially important regarding priority queues, since in this
library’s design, iterators are practically the only way to manipulate them.
22.2.3.4

Point and Range Iteration

This library differentiates between two types of methods and iterators: point-type, and range-type. For example, find and
insert are point-type methods, since they each deal with a specific element; their returned iterators are point-type iterators.
begin and end are range-type methods, since they are not used to find a specific element, but rather to go over all elements in
a container object; their returned iterators are range-type iterators.
Most containers store elements in an order that is determined by their interface. Correspondingly, it is fine that their point-type
iterators are synonymous with their range-type iterators. For example, in the following snippet
std::for_each(c.find(1), c.find(5), foo);

two point-type iterators (returned by find) are used for a range-type purpose - going over all elements whose key is between 1
and 5.
Conversely, the above snippet makes no sense for self-organizing containers - ones that order (and reorder) their elements by
implementation. It would be nice to have a uniform iterator system that would allow the above snippet to compile only if it made
sense.
This could trivially be done by specializing std::for_each for the case of iterators returned by std::tr1::unordere
d_map, but this would only solve the problem for one algorithm and one container. Fundamentally, the problem is that one can
loop using a self-organizing container’s point-type iterators.
This library’s containers define two families of iterators: point_const_iterator and point_iterator are the iterator types returned by
point-type methods; const_iterator and iterator are the iterator types returned by range-type methods.
class <- some container ->
{
public:
...
typedef <- something -> const_iterator;
typedef <- something -> iterator;
typedef <- something -> point_const_iterator;
typedef <- something -> point_iterator;
...
public:
...
const_iterator begin () const;
iterator begin();

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point_const_iterator find(...) const;
point_iterator find(...);
};

For containers whose interface defines sequence order , it is very simple: point-type and range-type iterators are exactly the same,
which means that the above snippet will compile if it is used for an order-preserving associative container.
For self-organizing containers, however, (hash-based containers as a special example), the preceding snippet will not compile,
because their point-type iterators do not support operator++.
In any case, both for order-preserving and self-organizing containers, the following snippet will compile:
typename Cntnr::point_iterator it = c.find(2);

because a range-type iterator can always be converted to a point-type iterator.
Distingushing between iterator types also raises the point that a container’s iterators might have different invalidation rules
concerning their de-referencing abilities and movement abilities. This now corresponds exactly to the question of whether pointtype and range-type iterators are valid. As explained above, container_traits allows querying a container for its data
structure attributes. The iterator-invalidation guarantees are certainly a property of the underlying data structure, and so
container_traits::invalidation_guarantee

gives one of three pre-determined types that answer this query.

22.2.4

Examples

Additional code examples are provided in the source distribution, as part of the regression and performance testsuite.
22.2.4.1

Intermediate Use

• Basic use of maps: basic_map.cc
• Basic use of sets: basic_set.cc
• Conditionally erasing values from an associative container object: erase_if.cc
• Basic use of multimaps: basic_multimap.cc
• Basic use of multisets: basic_multiset.cc
• Basic use of priority queues: basic_priority_queue.cc
• Splitting and joining priority queues: priority_queue_split_join.cc
• Conditionally erasing values from a priority queue: priority_queue_erase_if.cc
22.2.4.2

Querying with container_traits

• Using container_traits to query about underlying data structure behavior: assoc_container_traits.cc
• A non-compiling example showing wrong use of finding keys in hash-based containers: hash_find_neg.cc
• Using container_traits to query about underlying data structure behavior: priority_queue_container_traits.
cc

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By Container Method

22.2.4.3.1
22.2.4.3.1.1

Hash-Based
size Related

• Setting the initial size of a hash-based container object: hash_initial_size.cc
• A non-compiling example showing how not to resize a hash-based container object: hash_resize_neg.cc
• Resizing the size of a hash-based container object: hash_resize.cc
• Showing an illegal resize of a hash-based container object: hash_illegal_resize.cc
• Changing the load factors of a hash-based container object: hash_load_set_change.cc
22.2.4.3.1.2

Hashing Function Related

• Using a modulo range-hashing function for the case of an unknown skewed key distribution: hash_mod.cc
• Writing a range-hashing functor for the case of a known skewed key distribution: shift_mask.cc
• Storing the hash value along with each key: store_hash.cc
• Writing a ranged-hash functor: ranged_hash.cc
22.2.4.3.2
22.2.4.3.2.1

Branch-Based
split or join Related

• Joining two tree-based container objects: tree_join.cc
• Splitting a PATRICIA trie container object: trie_split.cc
• Order statistics while joining two tree-based container objects: tree_order_statistics_join.cc
22.2.4.3.2.2

Node Invariants

• Using trees for order statistics: tree_order_statistics.cc
• Augmenting trees to support operations on line intervals: tree_intervals.cc
22.2.4.3.2.3

trie

• Using a PATRICIA trie for DNA strings: trie_dna.cc
• Using a PATRICIA trie for finding all entries whose key matches a given prefix: trie_prefix_search.cc
22.2.4.3.3

Priority Queues

• Cross referencing an associative container and a priority queue: priority_queue_xref.cc
• Cross referencing a vector and a priority queue using a very simple version of Dijkstra’s shortest path algorithm: priority_
queue_dijkstra.cc

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Design

22.3.1

Concepts

22.3.1.1

Null Policy Classes

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Associative containers are typically parametrized by various policies. For example, a hash-based associative container is parametrized
by a hash-functor, transforming each key into an non-negative numerical type. Each such value is then further mapped into a
position within the table. The mapping of a key into a position within the table is therefore a two-step process.
In some cases, instantiations are redundant. For example, when the keys are integers, it is possible to use a redundant hash policy,
which transforms each key into its value.
In some other cases, these policies are irrelevant. For example, a hash-based associative container might transform keys into
positions within a table by a different method than the two-step method described above. In such a case, the hash functor is
simply irrelevant.
When a policy is either redundant or irrelevant, it can be replaced by null_type.
For example, a set is an associative container with one of its template parameters (the one for the mapped type) replaced with
null_type. Other places simplifications are made possible with this technique include node updates in tree and trie data
structures, and hash and probe functions for hash data structures.
22.3.1.2
22.3.1.2.1

Map and Set Semantics
Distinguishing Between Maps and Sets

Anyone familiar with the standard knows that there are four kinds of associative containers: maps, sets, multimaps, and multisets.
The map datatype associates each key to some data.
Sets are associative containers that simply store keys - they do not map them to anything. In the standard, each map class has a
corresponding set class. E.g., std::map maps each int to a char, but std::set simply
stores ints. In this library, however, there are no distinct classes for maps and sets. Instead, an associative container’s Mapped
template parameter is a policy: if it is instantiated by null_type, then it is a "set"; otherwise, it is a "map". E.g.,
cc_hash_table

is a "map" mapping each int value to a char, but
cc_hash_table

is a type that uniquely stores int values.
Once the Mapped template parameter is instantiated by null_type, then the "set" acts very similarly to the standard’s sets it does not map each key to a distinct null_type object. Also, , the container’s value_type is essentially its key_type - just as
with the standard’s sets .
The standard’s multimaps and multisets allow, respectively, non-uniquely mapping keys and non-uniquely storing keys. As
discussed, the reasons why this might be necessary are 1) that a key might be decomposed into a primary key and a secondary
key, 2) that a key might appear more than once, or 3) any arbitrary combination of 1)s and 2)s. Correspondingly, one should use
1) "maps" mapping primary keys to secondary keys, 2) "maps" mapping keys to size types, or 3) any arbitrary combination of
1)s and 2)s. Thus, for example, an std::multiset might be used to store multiple instances of integers, but using
this library’s containers, one might use
tree

i.e., a map of ints to size_ts.
These "multimaps" and "multisets" might be confusing to anyone familiar with the standard’s std::multimap and std::
multiset, because there is no clear correspondence between the two. For example, in some cases where one uses std::
multiset in the standard, one might use in this library a "multimap" of "multisets" - i.e., a container that maps primary keys
each to an associative container that maps each secondary key to the number of times it occurs.
When one uses a "multimap," one should choose with care the type of container used for secondary keys.

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Alternatives to std::multiset and std::multimap

Brace onself: this library does not contain containers like std::multimap or std::multiset. Instead, these data structures can be synthesized via manipulation of the Mapped template parameter.
One maps the unique part of a key - the primary key, into an associative-container of the (originally) non-unique parts of the key the secondary key. A primary associative-container is an associative container of primary keys; a secondary associative-container
is an associative container of secondary keys.
Stepping back a bit, and starting in from the beginning.
Maps (or sets) allow mapping (or storing) unique-key values. The standard library also supplies associative containers which
map (or store) multiple values with equivalent keys: std::multimap, std::multiset, std::tr1::unordered_mu
ltimap, and unordered_multiset. We first discuss how these might be used, then why we think it is best to avoid them.
Suppose one builds a simple bank-account application that records for each client (identified by an std::string) and accountid (marked by an unsigned long) - the balance in the account (described by a float). Suppose further that ordering this information
is not useful, so a hash-based container is preferable to a tree based container. Then one can use
std::tr1::unordered_map, float, ...>

which hashes every combination of client and account-id. This might work well, except for the fact that it is now impossible to
efficiently list all of the accounts of a specific client (this would practically require iterating over all entries). Instead, one can use
std::tr1::unordered_multimap, float, ...>

which hashes every client, and decides equivalence based on client only. This will ensure that all accounts belonging to a specific
user are stored consecutively.
Also, suppose one wants an integers’ priority queue (a container that supports push, pop, and top operations, the last of which
returns the largest int) that also supports operations such as find and lower_bound. A reasonable solution is to build an
adapter over std::set. In this adapter, push will just call the tree-based associative container’s insert method;
pop will call its end method, and use it to return the preceding element (which must be the largest). Then this might work well,
except that the container object cannot hold multiple instances of the same integer (push(4), will be a no-op if 4 is already in
the container object). If multiple keys are necessary, then one might build the adapter over an std::multiset.
The standard library’s non-unique-mapping containers are useful when (1) a key can be decomposed in to a primary key and a
secondary key, (2) a key is needed multiple times, or (3) any combination of (1) and (2).
The graphic below shows how the standard library’s container design works internally; in this figure nodes shaded equally
represent equivalent-key values. Equivalent keys are stored consecutively using the properties of the underlying data structure:
binary search trees (label A) store equivalent-key values consecutively (in the sense of an in-order walk) naturally; collisionchaining hash tables (label B) store equivalent-key values in the same bucket, the bucket can be arranged so that equivalent-key
values are consecutive.

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Figure 22.8: Non-unique Mapping Standard Containers
Put differently, the standards’ non-unique mapping associative-containers are associative containers that map primary keys to
linked lists that are embedded into the container. The graphic below shows again the two containers from the first graphic above,
this time with the embedded linked lists of the grayed nodes marked explicitly.

Figure 22.9: Effect of embedded lists in std::multimap
These embedded linked lists have several disadvantages.

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1. The underlying data structure embeds the linked lists according to its own consideration, which means that the search path
for a value might include several different equivalent-key values. For example, the search path for the the black node in
either of the first graphic, labels A or B, includes more than a single gray node.
2. The links of the linked lists are the underlying data structures’ nodes, which typically are quite structured. In the case of
tree-based containers (the grapic above, label B), each "link" is actually a node with three pointers (one to a parent and two
to children), and a relatively-complicated iteration algorithm. The linked lists, therefore, can take up quite a lot of memory,
and iterating over all values equal to a given key (through the return value of the standard library’s equal_range) can
be expensive.
3. The primary key is stored multiply; this uses more memory.
4. Finally, the interface of this design excludes several useful underlying data structures. Of all the unordered self-organizing
data structures, practically only collision-chaining hash tables can (efficiently) guarantee that equivalent-key values are
stored consecutively.
The above reasons hold even when the ratio of secondary keys to primary keys (or average number of identical keys) is small,
but when it is large, there are more severe problems:
1. The underlying data structures order the links inside each embedded linked-lists according to their internal considerations,
which effectively means that each of the links is unordered. Irrespective of the underlying data structure, searching for a
specific value can degrade to linear complexity.
2. Similarly to the above point, it is impossible to apply to the secondary keys considerations that apply to primary keys. For
example, it is not possible to maintain secondary keys by sorted order.
3. While the interface "understands" that all equivalent-key values constitute a distinct list (through equal_range), the
underlying data structure typically does not. This means that operations such as erasing from a tree-based container all
values whose keys are equivalent to a a given key can be super-linear in the size of the tree; this is also true also for several
other operations that target a specific list.
In this library, all associative containers map (or store) unique-key values. One can (1) map primary keys to secondary associativecontainers (containers of secondary keys) or non-associative containers (2) map identical keys to a size-type representing the
number of times they occur, or (3) any combination of (1) and (2). Instead of allowing multiple equivalent-key values, this
library supplies associative containers based on underlying data structures that are suitable as secondary associative-containers.
In the figure below, labels A and B show the equivalent underlying data structures in this library, as mapped to the first graphic
above. Labels A and B, respectively. Each shaded box represents some size-type or secondary associative-container.

Figure 22.10: Non-unique Mapping Containers

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In the first example above, then, one would use an associative container mapping each user to an associative container which
maps each application id to a start time (see example/basic_multimap.cc); in the second example, one would use an
associative container mapping each int to some size-type indicating the number of times it logically occurs (see example/
basic_multiset.cc.
See the discussion in list-based container types for containers especially suited as secondary associative-containers.
22.3.1.3
22.3.1.3.1

Iterator Semantics
Point and Range Iterators

Iterator concepts are bifurcated in this design, and are comprised of point-type and range-type iteration.
A point-type iterator is an iterator that refers to a specific element as returned through an associative-container’s find method.
A range-type iterator is an iterator that is used to go over a sequence of elements, as returned by a container’s find method.
A point-type method is a method that returns a point-type iterator; a range-type method is a method that returns a range-type
iterator.
For most containers, these types are synonymous; for self-organizing containers, such as hash-based containers or priority queues,
these are inherently different (in any implementation, including that of C++ standard library components), but in this design, it
is made explicit. They are distinct types.
22.3.1.3.2

Distinguishing Point and Range Iterators

When using this library, is necessary to differentiate between two types of methods and iterators: point-type methods and iterators,
and range-type methods and iterators. Each associative container’s interface includes the methods:
point_const_iterator
find(const_key_reference r_key) const;
point_iterator
find(const_key_reference r_key);
std::pair
insert(const_reference r_val);

The relationship between these iterator types varies between container types. The figure below shows the most general invariant
between point-type and range-type iterators: In A iterator, can always be converted to point_iterator. In B shows
invariants for order-preserving containers: point-type iterators are synonymous with range-type iterators. Orthogonally, Cshows
invariants for "set" containers: iterators are synonymous with const iterators.

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Figure 22.11: Point Iterator Hierarchy
Note that point-type iterators in self-organizing containers (hash-based associative containers) lack movement operators, such as
operator++ - in fact, this is the reason why this library differentiates from the standard C++ librarys design on this point.
Typically, one can determine an iterator’s movement capabilities using std::iterator_traitsiterator_cat
egory, which is a struct indicating the iterator’s movement capabilities. Unfortunately, none of the standard predefined
categories reflect a pointer’s not having any movement capabilities whatsoever. Consequently, pb_ds adds a type trivial_i
terator_tag (whose name is taken from a concept in C++ standardese, which is the category of iterators with no movement
capabilities.) All other standard C++ library tags, such as forward_iterator_tag retain their common use.
22.3.1.3.3

Invalidation Guarantees

If one manipulates a container object, then iterators previously obtained from it can be invalidated. In some cases a previouslyobtained iterator cannot be de-referenced; in other cases, the iterator’s next or previous element might have changed unpredictably. This corresponds exactly to the question whether a point-type or range-type iterator (see previous concept) is valid or
not. In this design, one can query a container (in compile time) about its invalidation guarantees.

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Given three different types of associative containers, a modifying operation (in that example, erase) invalidated iterators in
three different ways: the iterator of one container remained completely valid - it could be de-referenced and incremented; the
iterator of a different container could not even be de-referenced; the iterator of the third container could be de-referenced, but its
"next" iterator changed unpredictably.
Distinguishing between find and range types allows fine-grained invalidation guarantees, because these questions correspond
exactly to the question of whether point-type iterators and range-type iterators are valid. The graphic below shows tags corresponding to different types of invalidation guarantees.
__gnu_pbds::basic_invalidation_guarantee

__gnu_pbds::point_invalidation_guarantee

__gnu_pbds::range_invalidation_guarantee

Figure 22.12: Invalidation Guarantee Tags Hierarchy
• basic_invalidation_guarantee corresponds to a basic guarantee that a point-type iterator, a found pointer, or a
found reference, remains valid as long as the container object is not modified.
• point_invalidation_guarantee corresponds to a guarantee that a point-type iterator, a found pointer, or a found
reference, remains valid even if the container object is modified.
• range_invalidation_guarantee corresponds to a guarantee that a range-type iterator remains valid even if the container object is modified.
To find the invalidation guarantee of a container, one can use
typename container_traits::invalidation_guarantee

Note that this hierarchy corresponds to the logic it represents: if a container has range-invalidation guarantees, then it must also
have find invalidation guarantees; correspondingly, its invalidation guarantee (in this case range_invalidation_guaran
tee) can be cast to its base class (in this case point_invalidation_guarantee). This means that this this hierarchy can
be used easily using standard metaprogramming techniques, by specializing on the type of invalidation_guarantee.
These types of problems were addressed, in a more general setting, in [81] - Item 2. In our opinion, an invalidation-guarantee
hierarchy would solve these problems in all container types - not just associative containers.
22.3.1.4

Genericity

The design attempts to address the following problem of data-structure genericity. When writing a function manipulating a
generic container object, what is the behavior of the object? Suppose one writes
template
void
some_op_sequence(Cntnr &r_container)
{
...
}

then one needs to address the following questions in the body of some_op_sequence:

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• Which types and methods does Cntnr support? Containers based on hash tables can be queries for the hash-functor type and
object; this is meaningless for tree-based containers. Containers based on trees can be split, joined, or can erase iterators and
return the following iterator; this cannot be done by hash-based containers.
• What are the exception and invalidation guarantees of Cntnr? A container based on a probing hash-table invalidates all
iterators when it is modified; this is not the case for containers based on node-based trees. Containers based on a node-based
tree can be split or joined without exceptions; this is not the case for containers based on vector-based trees.
• How does the container maintain its elements? Tree-based and Trie-based containers store elements by key order; others,
typically, do not. A container based on a splay trees or lists with update policies "cache" "frequently accessed" elements;
containers based on most other underlying data structures do not.
• How does one query a container about characteristics and capabilities? What is the relationship between two different data
structures, if anything?
The remainder of this section explains these issues in detail.
22.3.1.4.1

Tag

Tags are very useful for manipulating generic types. For example, if It is an iterator class, then typename It::itera
tor_category or typename std::iterator_traits::iterator_category will yield its category, and
typename std::iterator_traits::value_type will yield its value type.
This library contains a container tag hierarchy corresponding to the diagram below.

__gnu_pbds::tree_tag

__gnu_pbds::basic_branch_tag

__gnu_pbds::trie_tag

__gnu_pbds::basic_hash_tag

__gnu_pbds::cc_hash_ta

__gnu_pbds::list_update_tag

__gnu_pbds::gp_hash_ta

__gnu_pbds::associative_tag

__gnu_pbds::binary_heap_tag

__gnu_pbds::binomial_heap_tag

__gnu_pbds::container_tag

__gnu_pbds::priority_queue_tag

__gnu_pbds::pairing_heap_tag

__gnu_pbds::rc_binomial_heap_tag

__gnu_pbds::sequence_tag

__gnu_pbds::thin_heap_tag

__gnu_pbds::string_tag

Figure 22.13: Container Tag Hierarchy
Given any container Cntnr, the tag of the underlying data structure can be found via typename Cntnr::container_cat
egory.

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Traits

Additionally, a traits mechanism can be used to query a container type for its attributes. Given any container Cntnr, then
 is a traits class identifying the properties of the container.
To find if a container can throw when a key is erased (which is true for vector-based trees, for example), one can use
container_traits::erase_can_throw

Some of the definitions in container_traits are dependent on other definitions. If container_traits:
:order_preserving is true (which is the case for containers based on trees and tries), then the container can be split
or joined; in this case, container_traits::split_join_can_throw indicates whether splits or joins can
throw exceptions (which is true for vector-based trees); otherwise container_traits::split_join_can_t
hrow will yield a compilation error. (This is somewhat similar to a compile-time version of the COM model).

22.3.2

By Container

22.3.2.1

hash

22.3.2.1.1

Interface

The collision-chaining hash-based container has the following declaration.
template<
typename Key,
typename Mapped,
typename Hash_Fn = std::hash,
typename Eq_Fn = std::equal_to,
typename Comb_Hash_Fn = direct_mask_range_hashing<>
typename Resize_Policy = default explained below.
bool Store_Hash = false,
typename Allocator = std::allocator >
class cc_hash_table;

The parameters have the following meaning:
1. Key is the key type.
2. Mapped is the mapped-policy.
3. Hash_Fn is a key hashing functor.
4. Eq_Fn is a key equivalence functor.
5. Comb_Hash_Fn is a range-hashing_functor; it describes how to translate hash values into positions within the table.
6. Resize_Policy describes how a container object should change its internal size.
7. Store_Hash indicates whether the hash value should be stored with each entry.
8. Allocator is an allocator type.
The probing hash-based container has the following declaration.
template<
typename Key,
typename Mapped,
typename Hash_Fn = std::hash,
typename Eq_Fn = std::equal_to,
typename Comb_Probe_Fn = direct_mask_range_hashing<>
typename Probe_Fn = default explained below.

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typename Resize_Policy = default explained below.
bool Store_Hash = false,
typename Allocator = std::allocator >
class gp_hash_table;

The parameters are identical to those of the collision-chaining container, except for the following.
1. Comb_Probe_Fn describes how to transform a probe sequence into a sequence of positions within the table.
2. Probe_Fn describes a probe sequence policy.
Some of the default template values depend on the values of other parameters, and are explained below.
22.3.2.1.2

Details

22.3.2.1.2.1

Hash Policies

22.3.2.1.2.2

General

Following is an explanation of some functions which hashing involves. The graphic below illustrates the discussion.

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Figure 22.14: Hash functions, ranged-hash functions, and range-hashing functions
Let U be a domain (e.g., the integers, or the strings of 3 characters). A hash-table algorithm needs to map elements of U
"uniformly" into the range [0,..., m - 1] (where m is a non-negative integral value, and is, in general, time varying). I.e., the
algorithm needs a ranged-hash function
f : U × Z+ → Z+
such that for any u in U ,
0 ≤ f(u, m) ≤ m - 1
and which has "good uniformity" properties (say [77].) One common solution is to use the composition of the hash function
h : U → Z+ ,
which maps elements of U into the non-negative integrals, and

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g : Z+ × Z+ → Z+ ,
which maps a non-negative hash value, and a non-negative range upper-bound into a non-negative integral in the range between
0 (inclusive) and the range upper bound (exclusive), i.e., for any r in Z+ ,
0 ≤ g(r, m) ≤ m - 1
The resulting ranged-hash function, is
f(u , m) = g(h(u), m)
E QUATION 22.1: Ranged Hash Function
From the above, it is obvious that given g and h, f can always be composed (however the converse is not true). The standard’s
hash-based containers allow specifying a hash function, and use a hard-wired range-hashing function; the ranged-hash function
is implicitly composed.
The above describes the case where a key is to be mapped into a single position within a hash table, e.g., in a collision-chaining
table. In other cases, a key is to be mapped into a sequence of positions within a table, e.g., in a probing table. Similar terms
apply in this case: the table requires a ranged probe function, mapping a key into a sequence of positions withing the table.
This is typically achieved by composing a hash function mapping the key into a non-negative integral type, a probe function
transforming the hash value into a sequence of hash values, and a range-hashing function transforming the sequence of hash
values into a sequence of positions.
22.3.2.1.2.3

Range Hashing

Some common choices for range-hashing functions are the division, multiplication, and middle-square methods ([77]), defined
as
g(r, m) = r mod m
E QUATION 22.2: Range-Hashing, Division Method
g(r, m) = d u/v ( a r mod v ) e
and
g(r, m) = d u/v ( r2 mod v ) e
respectively, for some positive integrals u and v (typically powers of 2), and some a. Each of these range-hashing functions works
best for some different setting.
The division method (see above) is a very common choice. However, even this single method can be implemented in two very
different ways. It is possible to implement using the low level % (modulo) operation (for any m), or the low level & (bit-mask)
operation (for the case where m is a power of 2), i.e.,
g(r, m) = r % m
E QUATION 22.3: Division via Prime Modulo
and
g(r, m) = r & m - 1, (with m = 2k for some k)
E QUATION 22.4: Division via Bit Mask
respectively.
The % (modulo) implementation has the advantage that for m a prime far from a power of 2, g(r, m) is affected by all the bits of
r (minimizing the chance of collision). It has the disadvantage of using the costly modulo operation. This method is hard-wired
into SGI’s implementation .
The & (bit-mask) implementation has the advantage of relying on the fast bit-wise and operation. It has the disadvantage that for
g(r, m) is affected only by the low order bits of r. This method is hard-wired into Dinkumware’s implementation.

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Ranged Hash

In cases it is beneficial to allow the client to directly specify a ranged-hash hash function. It is true, that the writer of the rangedhash function cannot rely on the values of m having specific numerical properties suitable for hashing (in the sense used in [77]),
since the values of m are determined by a resize policy with possibly orthogonal considerations.
There are two cases where a ranged-hash function can be superior. The firs is when using perfect hashing: the second is when
the values of m can be used to estimate the "general" number of distinct values required. This is described in the following.
Let
s = [ s0 ,..., st - 1 ]
be a string of t characters, each of which is from domain S. Consider the following ranged-hash function:
f1 (s, m) = ∑ i = 0 t - 1 si ai mod m
E QUATION 22.5: A Standard String Hash Function
where a is some non-negative integral value. This is the standard string-hashing function used in SGI’s implementation (with a =
5). Its advantage is that it takes into account all of the characters of the string.
Now assume that s is the string representation of a of a long DNA sequence (and so S = {’A’, ’C’, ’G’, ’T’}). In this case,
scanning the entire string might be prohibitively expensive. A possible alternative might be to use only the first k characters of
the string, where
|S|k ≥ m ,
i.e., using the hash function
f2 (s, m) = ∑ i = 0 k - 1 si ai mod m
E QUATION 22.6: Only k String DNA Hash
requiring scanning over only
k = log4 ( m )
characters.
Other more elaborate hash-functions might scan k characters starting at a random position (determined at each resize), or scanning
k random positions (determined at each resize), i.e., using
f3 (s, m) = ∑ i = r 0r0 + k - 1 si ai mod m ,
or
f4 (s, m) = ∑ i = 0 k - 1 sr i ari mod m ,
respectively, for r0 ,..., rk-1 each in the (inclusive) range [0,...,t-1].
It should be noted that the above functions cannot be decomposed as per a ranged hash composed of hash and range hashing.
22.3.2.1.2.5

Implementation

This sub-subsection describes the implementation of the above in this library. It first explains range-hashing functions in collisionchaining tables, then ranged-hash functions in collision-chaining tables, then probing-based tables, and finally lists the relevant
classes in this library.

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Range-Hashing and Ranged-Hashes in Collision-Chaining Tables

cc_hash_table is parametrized by Hash_Fn and Comb_Hash_Fn, a hash functor and a combining hash functor, respectively.
In general, Comb_Hash_Fn is considered a range-hashing functor. cc_hash_table synthesizes a ranged-hash function
from Hash_Fn and Comb_Hash_Fn. The figure below shows an insert sequence diagram for this case. The user inserts
an element (point A), the container transforms the key into a non-negative integral using the hash functor (points B and C), and
transforms the result into a position using the combining functor (points D and E).

Figure 22.15: Insert hash sequence diagram
If cc_hash_table’s hash-functor, Hash_Fn is instantiated by null_type , then Comb_Hash_Fn is taken to be a rangedhash function. The graphic below shows an insert sequence diagram. The user inserts an element (point A), the container
transforms the key into a position using the combining functor (points B and C).

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Figure 22.16: Insert hash sequence diagram with a null policy

22.3.2.1.2.7

Probing tables

gp_hash_table is parametrized by Hash_Fn, Probe_Fn, and Comb_Probe_Fn. As before, if Hash_Fn and Pro
be_Fn are both null_type, then Comb_Probe_Fn is a ranged-probe functor. Otherwise, Hash_Fn is a hash functor,
Probe_Fn is a functor for offsets from a hash value, and Comb_Probe_Fn transforms a probe sequence into a sequence of
positions within the table.
22.3.2.1.2.8

Pre-Defined Policies

This library contains some pre-defined classes implementing range-hashing and probing functions:
1. direct_mask_range_hashing and direct_mod_range_hashing are range-hashing functions based on a bitmask and a modulo operation, respectively.
2. linear_probe_fn, and quadratic_probe_fn are a linear probe and a quadratic probe function, respectively.
The graphic below shows the relationships.

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Figure 22.17: Hash policy class diagram

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Resize Policies
General

Hash-tables, as opposed to trees, do not naturally grow or shrink. It is necessary to specify policies to determine how and when
a hash table should change its size. Usually, resize policies can be decomposed into orthogonal policies:
1. A size policy indicating how a hash table should grow (e.g., it should multiply by powers of 2).
2. A trigger policy indicating when a hash table should grow (e.g., a load factor is exceeded).
22.3.2.1.2.11

Size Policies

Size policies determine how a hash table changes size. These policies are simple, and there are relatively few sensible options. An
exponential-size policy (with the initial size and growth factors both powers of 2) works well with a mask-based range-hashing
function, and is the hard-wired policy used by Dinkumware. A prime-list based policy works well with a modulo-prime range
hashing function and is the hard-wired policy used by SGI’s implementation.
22.3.2.1.2.12

Trigger Policies

Trigger policies determine when a hash table changes size. Following is a description of two policies: load-check policies, and
collision-check policies.
Load-check policies are straightforward. The user specifies two factors, Amin and Amax , and the hash table maintains the invariant
that
Amin ≤ (number of stored elements) / (hash-table size) ≤ Amax
Collision-check policies work in the opposite direction of load-check policies. They focus on keeping the number of collisions
moderate and hoping that the size of the table will not grow very large, instead of keeping a moderate load-factor and hoping
that the number of collisions will be small. A maximal collision-check policy resizes when the longest probe-sequence grows
too large.
Consider the graphic below. Let the size of the hash table be denoted by m, the length of a probe sequence be denoted by k, and
some load factor be denoted by A. We would like to calculate the minimal length of k, such that if there were A m elements in
the hash table, a probe sequence of length k would be found with probability at most 1/m.

Figure 22.18: Balls and bins
Denote the probability that a probe sequence of length k appears in bin i by pi , the length of the probe sequence of bin i by li , and
assume uniform distribution. Then
p1 =
E QUATION 22.7: Probability of Probe Sequence of Length k

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P(l1 ≥ k) =
P(l1 ≥ α ( 1 + k / α - 1) ≤ (a)
e ˆ ( - ( α ( k / α - 1 )2 ) /2)
where (a) follows from the Chernoff bound ([85]). To calculate the probability that some bin contains a probe sequence greater
than k, we note that the li are negatively-dependent ([67]) . Let I(.) denote the indicator function. Then
P( existsi li ≥ k ) =
E QUATION 22.8: Probability Probe Sequence in Some Bin
P ( ∑ i = 1 m I(li ≥ k) ≥ 1 ) =
P ( ∑ i = 1 m I ( li ≥ k ) ≥ m p1 ( 1 + 1 / (m p1 ) - 1 ) ) ≤ (a)
e ˆ ( ( - m p1 ( 1 / (m p1 ) - 1 ) 2 ) / 2 ) ,
where (a) follows from the fact that the Chernoff bound can be applied to negatively-dependent variables ([67]). Inserting the
first probability equation into the second one, and equating with 1/m, we obtain
√
k ~ ( 2 α ln 2 m ln(m) ) ) .
22.3.2.1.2.13

Implementation

This sub-subsection describes the implementation of the above in this library. It first describes resize policies and their decomposition into trigger and size policies, then describes pre-defined classes, and finally discusses controlled access the policies’
internals.
22.3.2.1.2.14

Decomposition

Each hash-based container is parametrized by a Resize_Policy parameter; the container derives publicly from Resize_
Policy. For example:
cc_hash_table : public Resize_Policy

As a container object is modified, it continuously notifies its Resize_Policy base of internal changes (e.g., collisions encountered and elements being inserted). It queries its Resize_Policy base whether it needs to be resized, and if so, to what
size.
The graphic below shows a (possible) sequence diagram of an insert operation. The user inserts an element; the hash table notifies
its resize policy that a search has started (point A); in this case, a single collision is encountered - the table notifies its resize
policy of this (point B); the container finally notifies its resize policy that the search has ended (point C); it then queries its resize
policy whether a resize is needed, and if so, what is the new size (points D to G); following the resize, it notifies the policy that a
resize has completed (point H); finally, the element is inserted, and the policy notified (point I).

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Figure 22.19: Insert resize sequence diagram

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In practice, a resize policy can be usually orthogonally decomposed to a size policy and a trigger policy. Consequently, the library
contains a single class for instantiating a resize policy: hash_standard_resize_policy is parametrized by Size_Pol
icy and Trigger_Policy, derives publicly from both, and acts as a standard delegate ([71]) to these policies.
The two graphics immediately below show sequence diagrams illustrating the interaction between the standard resize policy and
its trigger and size policies, respectively.

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Figure 22.20: Standard resize policy trigger sequence diagram

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Figure 22.21: Standard resize policy size sequence diagram

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Predefined Policies

The library includes the following instantiations of size and trigger policies:
1. hash_load_check_resize_trigger implements a load check trigger policy.
2. cc_hash_max_collision_check_resize_trigger implements a collision check trigger policy.
3. hash_exponential_size_policy implements an exponential-size policy (which should be used with mask range
hashing).
4. hash_prime_size_policy implementing a size policy based on a sequence of primes (which should be used with
mod range hashing
The graphic below gives an overall picture of the resize-related classes. basic_hash_table is parametrized by Resize_P
olicy, which it subclasses publicly. This class is currently instantiated only by hash_standard_resize_policy. has
h_standard_resize_policy itself is parametrized by Trigger_Policy and Size_Policy. Currently, Trigger_
Policy is instantiated by hash_load_check_resize_trigger, or cc_hash_max_collision_check_resize
_trigger; Size_Policy is instantiated by hash_exponential_size_policy, or hash_prime_size_policy.
22.3.2.1.2.16

Controling Access to Internals

There are cases where (controlled) access to resize policies’ internals is beneficial. E.g., it is sometimes useful to query a hashtable for the table’s actual size (as opposed to its size() - the number of values it currently holds); it is sometimes useful to set
a table’s initial size, externally resize it, or change load factors.
Clearly, supporting such methods both decreases the encapsulation of hash-based containers, and increases the diversity between
different associative-containers’ interfaces. Conversely, omitting such methods can decrease containers’ flexibility.
In order to avoid, to the extent possible, the above conflict, the hash-based containers themselves do not address any of these
questions; this is deferred to the resize policies, which are easier to change or replace. Thus, for example, neither cc_hash_t
able nor gp_hash_table contain methods for querying the actual size of the table; this is deferred to hash_standard_
resize_policy.
Furthermore, the policies themselves are parametrized by template arguments that determine the methods they support ( [56]
shows techniques for doing so). hash_standard_resize_policy is parametrized by External_Size_Access that
determines whether it supports methods for querying the actual size of the table or resizing it. hash_load_check_resi
ze_trigger is parametrized by External_Load_Access that determines whether it supports methods for querying or
modifying the loads. cc_hash_max_collision_check_resize_trigger is parametrized by External_Load_Ac
cess that determines whether it supports methods for querying the load.
Some operations, for example, resizing a container at run time, or changing the load factors of a load-check trigger policy,
require the container itself to resize. As mentioned above, the hash-based containers themselves do not contain these types of
methods, only their resize policies. Consequently, there must be some mechanism for a resize policy to manipulate the hash-based
container. As the hash-based container is a subclass of the resize policy, this is done through virtual methods. Each hash-based
container has a private virtual method:
virtual void
do_resize
(size_type new_size);

which resizes the container. Implementations of Resize_Policy can export public methods for resizing the container externally; these methods internally call do_resize to resize the table.
22.3.2.1.2.17

Policy Interactions

Hash-tables are unfortunately especially susceptible to choice of policies. One of the more complicated aspects of this is that
poor combinations of good policies can form a poor container. Following are some considerations.

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probe/size/trigger

Some combinations do not work well for probing containers. For example, combining a quadratic probe policy with an exponential size policy can yield a poor container: when an element is inserted, a trigger policy might decide that there is no need to
resize, as the table still contains unused entries; the probe sequence, however, might never reach any of the unused entries.
Unfortunately, this library cannot detect such problems at compilation (they are halting reducible). It therefore defines an exception class insert_error to throw an exception in this case.
22.3.2.1.2.19

hash/trigger

Some trigger policies are especially susceptible to poor hash functions. Suppose, as an extreme case, that the hash function
transforms each key to the same hash value. After some inserts, a collision detecting policy will always indicate that the container
needs to grow.
The library, therefore, by design, limits each operation to one resize. For each insert, for example, it queries only once whether
a resize is needed.
22.3.2.1.2.20

equivalence functors/storing hash values/hash

cc_hash_table and gp_hash_table are parametrized by an equivalence functor and by a Store_Hash parameter. If
the latter parameter is true, then the container stores with each entry a hash value, and uses this value in case of collisions to
determine whether to apply a hash value. This can lower the cost of collision for some types, but increase the cost of collisions
for other types.
If a ranged-hash function or ranged probe function is directly supplied, however, then it makes no sense to store the hash value
with each entry. This library’s container will fail at compilation, by design, if this is attempted.
22.3.2.1.2.21

size/load-check trigger

Assume a size policy issues an increasing sequence of sizes a, a q, a q1 , a q2 , ... For example, an exponential size policy might
issue the sequence of sizes 8, 16, 32, 64, ...
If a load-check trigger policy is used, with loads α min and α max , respectively, then it is a good idea to have:
1. α max ~ 1 / q
2. α min < 1 / (2 q)
This will ensure that the amortized hash cost of each modifying operation is at most approximately 3.
α min ~ α max is, in any case, a bad choice, and α min > α
22.3.2.2
22.3.2.2.1

max

is horrendous.

tree
Interface

The tree-based container has the following declaration:
template<
typename Key,
typename Mapped,
typename Cmp_Fn = std::less,
typename Tag = rb_tree_tag,
template<
typename Const_Node_Iterator,
typename Node_Iterator,
typename Cmp_Fn_,
typename Allocator_>
class Node_Update = null_node_update,
typename Allocator = std::allocator >
class tree;

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The parameters have the following meaning:
1. Key is the key type.
2. Mapped is the mapped-policy.
3. Cmp_Fn is a key comparison functor
4. Tag specifies which underlying data structure to use.
5. Node_Update is a policy for updating node invariants.
6. Allocator is an allocator type.
The Tag parameter specifies which underlying data structure to use. Instantiating it by rb_tree_tag, splay_tree_tag,
or ov_tree_tag, specifies an underlying red-black tree, splay tree, or ordered-vector tree, respectively; any other tag is illegal.
Note that containers based on the former two contain more types and methods than the latter (e.g., reverse_iterator and
rbegin), and different exception and invalidation guarantees.
22.3.2.2.2
22.3.2.2.2.1

Details
Node Invariants

Consider the two trees in the graphic below, labels A and B. The first is a tree of floats; the second is a tree of pairs, each
signifying a geometric line interval. Each element in a tree is referred to as a node of the tree. Of course, each of these trees can
support the usual queries: the first can easily search for 0.4; the second can easily search for std::make_pair(10, 41).
Each of these trees can efficiently support other queries. The first can efficiently determine that the 2rd key in the tree is 0.3;
the second can efficiently determine whether any of its intervals overlaps
std::make_pair(29,42)

(useful in geometric applications or distributed file systems with leases, for example). It should be noted that an std::set can
only solve these types of problems with linear complexity.
In order to do so, each tree stores some metadata in each node, and maintains node invariants (see [66].) The first stores in
each node the size of the sub-tree rooted at the node; the second stores at each node the maximal endpoint of the intervals at the
sub-tree rooted at the node.

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Figure 22.22: Tree node invariants
Supporting such trees is difficult for a number of reasons:
1. There must be a way to specify what a node’s metadata should be (if any).
2. Various operations can invalidate node invariants. The graphic below shows how a right rotation, performed on A, results
in B, with nodes x and y having corrupted invariants (the grayed nodes in C). The graphic shows how an insert, performed
on D, results in E, with nodes x and y having corrupted invariants (the grayed nodes in F). It is not feasible to know outside
the tree the effect of an operation on the nodes of the tree.
3. The search paths of standard associative containers are defined by comparisons between keys, and not through metadata.
4. It is not feasible to know in advance which methods trees can support. Besides the usual find method, the first tree can
support a find_by_order method, while the second can support an overlaps method.

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Figure 22.23: Tree node invalidation
These problems are solved by a combination of two means: node iterators, and template-template node updater parameters.

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Node Iterators

Each tree-based container defines two additional iterator types, const_node_iterator and node_iterator. These
iterators allow descending from a node to one of its children. Node iterator allow search paths different than those determined
by the comparison functor. The tree supports the methods:
const_node_iterator
node_begin() const;
node_iterator
node_begin();
const_node_iterator
node_end() const;
node_iterator
node_end();

The first pairs return node iterators corresponding to the root node of the tree; the latter pair returns node iterators corresponding
to a just-after-leaf node.
22.3.2.2.2.3

Node Updator

The tree-based containers are parametrized by a Node_Update template-template parameter. A tree-based container instantiates Node_Update to some node_update class, and publicly subclasses node_update. The graphic below shows this
scheme, as well as some predefined policies (which are explained below).

Figure 22.24: A tree and its update policy
node_update (an instantiation of Node_Update) must define metadata_type as the type of metadata it requires. For
order statistics, e.g., metadata_type might be size_t. The tree defines within each node a metadata_type object.
node_update must also define the following method for restoring node invariants:

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void
operator()(node_iterator nd_it, const_node_iterator end_nd_it)

In this method, nd_it is a node_iterator corresponding to a node whose A) all descendants have valid invariants, and B)
its own invariants might be violated; end_nd_it is a const_node_iterator corresponding to a just-after-leaf node. This
method should correct the node invariants of the node pointed to by nd_it. For example, say node x in the graphic below label
A has an invalid invariant, but its’ children, y and z have valid invariants. After the invocation, all three nodes should have valid
invariants, as in label B.

Figure 22.25: Restoring node invariants
When a tree operation might invalidate some node invariant, it invokes this method in its node_update base to restore the
invariant. For example, the graphic below shows an insert operation (point A); the tree performs some operations, and calls
the update functor three times (points B, C, and D). (It is well known that any insert, erase, split or join, can restore
all node invariants by a small number of node invariant updates ([66]) .

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Figure 22.26: Insert update sequence
To complete the description of the scheme, three questions need to be answered:
1. How can a tree which supports order statistics define a method such as find_by_order?
2. How can the node updater base access methods of the tree?
3. How can the following cyclic dependency be resolved? node_update is a base class of the tree, yet it uses node iterators
defined in the tree (its child).
The first two questions are answered by the fact that node_update (an instantiation of Node_Update) is a public base class
of the tree. Consequently:
1. Any public methods of node_update are automatically methods of the tree ([56]). Thus an order-statistics node updater, tree_order_statistics_node_update defines the find_by_order method; any tree instantiated by
this policy consequently supports this method as well.
2. In C++, if a base class declares a method as virtual, it is virtual in its subclasses. If node_update needs to access
one of the tree’s methods, say the member function end, it simply declares that method as virtual abstract.
The cyclic dependency is solved through template-template parameters. Node_Update is parametrized by the tree’s node
iterators, its comparison functor, and its allocator type. Thus, instantiations of Node_Update have all information required.
This library assumes that constructing a metadata object and modifying it are exception free. Suppose that during some method,
say insert, a metadata-related operation (e.g., changing the value of a metadata) throws an exception. Ack! Rolling back the
method is unusually complex.

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Previously, a distinction was made between redundant policies and null policies. Node invariants show a case where null policies
are required.
Assume a regular tree is required, one which need not support order statistics or interval overlap queries. Seemingly, in this case
a redundant policy - a policy which doesn’t affect nodes’ contents would suffice. This, would lead to the following drawbacks:
1. Each node would carry a useless metadata object, wasting space.
2. The tree cannot know if its Node_Update policy actually modifies a node’s metadata (this is halting reducible). In the
graphic below, assume the shaded node is inserted. The tree would have to traverse the useless path shown to the root,
applying redundant updates all the way.

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Figure 22.27: Useless update path
A null policy class, null_node_update solves both these problems. The tree detects that node invariants are irrelevant, and
defines all accordingly.

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Split and Join

Tree-based containers support split and join methods. It is possible to split a tree so that it passes all nodes with keys larger than
a given key to a different tree. These methods have the following advantages over the alternative of externally inserting to the
destination tree and erasing from the source tree:
1. These methods are efficient - red-black trees are split and joined in poly-logarithmic complexity; ordered-vector trees are
split and joined at linear complexity. The alternatives have super-linear complexity.
2. Aside from orders of growth, these operations perform few allocations and de-allocations. For red-black trees, allocations
are not performed, and the methods are exception-free.
22.3.2.3
22.3.2.3.1

Trie
Interface

The trie-based container has the following declaration:
template,
typename Tag = pat_trie_tag,
template
class Node_Update = null_node_update,
typename Allocator = std::allocator >
class trie;

The parameters have the following meaning:
1. Key is the key type.
2. Mapped is the mapped-policy.
3. E_Access_Traits is described in below.
4. Tag specifies which underlying data structure to use, and is described shortly.
5. Node_Update is a policy for updating node invariants. This is described below.
6. Allocator is an allocator type.
The Tag parameter specifies which underlying data structure to use. Instantiating it by pat_trie_tag, specifies an underlying
PATRICIA trie (explained shortly); any other tag is currently illegal.
Following is a description of a (PATRICIA) trie (this implementation follows [90] and [69]).
A (PATRICIA) trie is similar to a tree, but with the following differences:
1. It explicitly views keys as a sequence of elements. E.g., a trie can view a string as a sequence of characters; a trie can view
a number as a sequence of bits.
2. It is not (necessarily) binary. Each node has fan-out n + 1, where n is the number of distinct elements.
3. It stores values only at leaf nodes.
4. Internal nodes have the properties that A) each has at least two children, and B) each shares the same prefix with any of its
descendant.

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A (PATRICIA) trie has some useful properties:
1. It can be configured to use large node fan-out, giving it very efficient find performance (albeit at insertion complexity and
size).
2. It works well for common-prefix keys.
3. It can support efficiently queries such as which keys match a certain prefix. This is sometimes useful in file systems and
routers, and for "type-ahead" aka predictive text matching on mobile devices.
22.3.2.3.2
22.3.2.3.2.1

Details
Element Access Traits

A trie inherently views its keys as sequences of elements. For example, a trie can view a string as a sequence of characters. A
trie needs to map each of n elements to a number in {0, n - 1}. For example, a trie can map a character c to
static_cast(c)

.
Seemingly, then, a trie can assume that its keys support (const) iterators, and that the value_type of this iterator can be cast
to a size_t. There are several reasons, though, to decouple the mechanism by which the trie accesses its keys’ elements from
the trie:
1. In some cases, the numerical value of an element is inappropriate. Consider a trie storing DNA strings. It is logical to use
a trie with a fan-out of 5 = 1 + |{’A’, ’C’, ’G’, ’T’}|. This requires mapping ’T’ to 3, though.
2. In some cases the keys’ iterators are different than what is needed. For example, a trie can be used to search for common
suffixes, by using strings’ reverse_iterator. As another example, a trie mapping UNICODE strings would have a
huge fan-out if each node would branch on a UNICODE character; instead, one can define an iterator iterating over 8-bit
(or less) groups.
trie is, consequently, parametrized by E_Access_Traits - traits which instruct how to access sequences’ elements. string
_trie_e_access_traits is a traits class for strings. Each such traits define some types, like:
typename E_Access_Traits::const_iterator

is a const iterator iterating over a key’s elements. The traits class must also define methods for obtaining an iterator to the first
and last element of a key.
The graphic below shows a (PATRICIA) trie resulting from inserting the words: "I wish that I could ever see a poem lovely as a
trie" (which, unfortunately, does not rhyme).
The leaf nodes contain values; each internal node contains two typename E_Access_Traits::const_iterator objects, indicating the maximal common prefix of all keys in the sub-tree. For example, the shaded internal node roots a sub-tree
with leafs "a" and "as". The maximal common prefix is "a". The internal node contains, consequently, to const iterators, one
pointing to ’a’, and the other to ’s’.

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Figure 22.28: A PATRICIA trie

22.3.2.3.2.2

Node Invariants

Trie-based containers support node invariants, as do tree-based containers. There are two minor differences, though, which,
unfortunately, thwart sharing them sharing the same node-updating policies:
1. A trie’s Node_Update template-template parameter is parametrized by E_Access_Traits, while a tree’s Node_Up
date template-template parameter is parametrized by Cmp_Fn.
2. Tree-based containers store values in all nodes, while trie-based containers (at least in this implementation) store values in
leafs.
The graphic below shows the scheme, as well as some predefined policies (which are explained below).

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Figure 22.29: A trie and its update policy
This library offers the following pre-defined trie node updating policies:
1. trie_order_statistics_node_update supports order statistics.
2. trie_prefix_search_node_update supports searching for ranges that match a given prefix.
3. null_node_update is the null node updater.
22.3.2.3.2.3

Split and Join

Trie-based containers support split and join methods; the rationale is equal to that of tree-based containers supporting these
methods.
22.3.2.4
22.3.2.4.1

List
Interface

The list-based container has the following declaration:

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template,
typename Update_Policy = move_to_front_lu_policy<>,
typename Allocator = std::allocator >
class list_update;

The parameters have the following meaning:
1. Key is the key type.
2. Mapped is the mapped-policy.
3. Eq_Fn is a key equivalence functor.
4. Update_Policy is a policy updating positions in the list based on access patterns. It is described in the following
subsection.
5. Allocator is an allocator type.
A list-based associative container is a container that stores elements in a linked-list. It does not order the elements by any
particular order related to the keys. List-based containers are primarily useful for creating "multimaps". In fact, list-based
containers are designed in this library expressly for this purpose.
List-based containers might also be useful for some rare cases, where a key is encapsulated to the extent that only key-equivalence
can be tested. Hash-based containers need to know how to transform a key into a size type, and tree-based containers need to know
if some key is larger than another. List-based associative containers, conversely, only need to know if two keys are equivalent.
Since a list-based associative container does not order elements by keys, is it possible to order the list in some useful manner?
Remarkably, many on-line competitive algorithms exist for reordering lists to reflect access prediction. (See [85] and [57]).
22.3.2.4.2
22.3.2.4.2.1

Details
Underlying Data Structure

The graphic below shows a simple list of integer keys. If we search for the integer 6, we are paying an overhead: the link with
key 6 is only the fifth link; if it were the first link, it could be accessed faster.

Figure 22.30: A simple list
List-update algorithms reorder lists as elements are accessed. They try to determine, by the access history, which keys to move
to the front of the list. Some of these algorithms require adding some metadata alongside each entry.
For example, in the graphic below label A shows the counter algorithm. Each node contains both a key and a count metadata
(shown in bold). When an element is accessed (e.g. 6) its count is incremented, as shown in label B. If the count reaches some
predetermined value, say 10, as shown in label C, the count is set to 0 and the node is moved to the front of the list, as in label D.

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Figure 22.31: The counter algorithm

22.3.2.4.2.2

Policies

this library allows instantiating lists with policies implementing any algorithm moving nodes to the front of the list (policies
implementing algorithms interchanging nodes are unsupported).
Associative containers based on lists are parametrized by a Update_Policy parameter. This parameter defines the type of
metadata each node contains, how to create the metadata, and how to decide, using this metadata, whether to move a node to the
front of the list. A list-based associative container object derives (publicly) from its update policy.
An instantiation of Update_Policy must define internally update_metadata as the metadata it requires. Internally, each
node of the list contains, besides the usual key and data, an instance of typename Update_Policy::update_metad
ata.
An instantiation of Update_Policy must define internally two operators:
update_metadata
operator()();
bool
operator()(update_metadata &);

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The first is called by the container object, when creating a new node, to create the node’s metadata. The second is called by
the container object, when a node is accessed ( when a find operation’s key is equivalent to the key of the node), to determine
whether to move the node to the front of the list.
The library contains two predefined implementations of list-update policies. The first is lu_counter_policy, which implements the counter algorithm described above. The second is lu_move_to_front_policy, which unconditionally move an
accessed element to the front of the list. The latter type is very useful in this library, since there is no need to associate metadata
with each element. (See [57]
22.3.2.4.2.3

Use in Multimaps

In this library, there are no equivalents for the standard’s multimaps and multisets; instead one uses an associative container
mapping primary keys to secondary keys.
List-based containers are especially useful as associative containers for secondary keys. In fact, they are implemented here
expressly for this purpose.
To begin with, these containers use very little per-entry structure memory overhead, since they can be implemented as singlylinked lists. (Arrays use even lower per-entry memory overhead, but they are less flexible in moving around entries, and have
weaker invalidation guarantees).
More importantly, though, list-based containers use very little per-container memory overhead. The memory overhead of an
empty list-based container is practically that of a pointer. This is important for when they are used as secondary associativecontainers in situations where the average ratio of secondary keys to primary keys is low (or even 1).
In order to reduce the per-container memory overhead as much as possible, they are implemented as closely as possible to
singly-linked lists.
1. List-based containers do not store internally the number of values that they hold. This means that their size method has
linear complexity (just like std::list). Note that finding the number of equivalent-key values in a standard multimap
also has linear complexity (because it must be done, via std::distance of the multimap’s equal_range method),
but usually with higher constants.
2. Most associative-container objects each hold a policy object (a hash-based container object holds a hash functor). Listbased containers, conversely, only have class-wide policy objects.
22.3.2.5
22.3.2.5.1

Priority Queue
Interface

The priority queue container has the following declaration:
template,
typename Tag = pairing_heap_tag,
typename Allocator = std::allocator >
class priority_queue;

The parameters have the following meaning:
1. Value_Type is the value type.
2. Cmp_Fn is a value comparison functor
3. Tag specifies which underlying data structure to use.
4. Allocator is an allocator type.

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The Tag parameter specifies which underlying data structure to use. Instantiating it bypairing_heap_tag,binary_hea
p_tag, binomial_heap_tag, rc_binomial_heap_tag, or thin_heap_tag, specifies, respectively, an underlying
pairing heap ([70]), binary heap ([66]), binomial heap ([66]), a binomial heap with a redundant binary counter ([80]), or a thin
heap ([75]).
As mentioned in the tutorial, __gnu_pbds::priority_queue shares most of the same interface with std::priorit
y_queue. E.g. if q is a priority queue of type Q, then q.top() will return the "largest" value in the container (according
to typename Q::cmp_fn). __gnu_pbds::priority_queue has a larger (and very slightly different) interface than
std::priority_queue, however, since typically push and pop are deemed insufficient for manipulating priority-queues.
Different settings require different priority-queue implementations which are described in later; see traits discusses ways to
differentiate between the different traits of different implementations.
22.3.2.5.2
22.3.2.5.2.1

Details
Iterators

There are many different underlying-data structures for implementing priority queues. Unfortunately, most such structures are
oriented towards making push and top efficient, and consequently don’t allow efficient access of other elements: for instance,
they cannot support an efficient find method. In the use case where it is important to both access and "do something with" an
arbitrary value, one would be out of luck. For example, many graph algorithms require modifying a value (typically increasing it
in the sense of the priority queue’s comparison functor).
In order to access and manipulate an arbitrary value in a priority queue, one needs to reference the internals of the priority queue
from some form of an associative container - this is unavoidable. Of course, in order to maintain the encapsulation of the priority
queue, this needs to be done in a way that minimizes exposure to implementation internals.
In this library the priority queue’s insert method returns an iterator, which if valid can be used for subsequent modify
and erase operations. This both preserves the priority queue’s encapsulation, and allows accessing arbitrary values (since the
returned iterators from the push operation can be stored in some form of associative container).
Priority queues’ iterators present a problem regarding their invalidation guarantees. One assumes that calling operator++ on
an iterator will associate it with the "next" value. Priority-queues are self-organizing: each operation changes what the "next"
value means. Consequently, it does not make sense that push will return an iterator that can be incremented - this can have no
possible use. Also, as in the case of hash-based containers, it is awkward to define if a subsequent push operation invalidates
a prior returned iterator: it invalidates it in the sense that its "next" value is not related to what it previously considered to be
its "next" value. However, it might not invalidate it, in the sense that it can be de-referenced and used for modify and erase
operations.
Similarly to the case of the other unordered associative containers, this library uses a distinction between point-type and range
type iterators. A priority queue’s iterator can always be converted to a point_iterator, and a const_iterator can
always be converted to a point_const_iterator.
The following snippet demonstrates manipulating an arbitrary value:
// A priority queue of integers.
priority_queue p;
// Insert some values into the priority queue.
priority_queue::point_iterator it = p.push(0);
p.push(1);
p.push(2);
// Now modify a value.
p.modify(it, 3);
assert(p.top() == 3);

It should be noted that an alternative design could embed an associative container in a priority queue. Could, but most probably
should not. To begin with, it should be noted that one could always encapsulate a priority queue and an associative container

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mapping values to priority queue iterators with no performance loss. One cannot, however, "un-encapsulate" a priority queue
embedding an associative container, which might lead to performance loss. Assume, that one needs to associate each value
with some data unrelated to priority queues. Then using this library’s design, one could use an associative container mapping
each value to a pair consisting of this data and a priority queue’s iterator. Using the embedded method would need to use two
associative containers. Similar problems might arise in cases where a value can reside simultaneously in many priority queues.
22.3.2.5.2.2

Underlying Data Structure

There are three main implementations of priority queues: the first employs a binary heap, typically one which uses a sequence;
the second uses a tree (or forest of trees), which is typically less structured than an associative container’s tree; the third simply
uses an associative container. These are shown in the graphic below, in labels A1 and A2, label B, and label C.

Figure 22.32: Underlying Priority-Queue Data-Structures.
Roughly speaking, any value that is both pushed and popped from a priority queue must incur a logarithmic expense (in the
amortized sense). Any priority queue implementation that would avoid this, would violate known bounds on comparison-based
sorting (see [66] and [64]).
Most implementations do not differ in the asymptotic amortized complexity of push and pop operations, but they differ in the
constants involved, in the complexity of other operations (e.g., modify), and in the worst-case complexity of single operations.
In general, the more "structured" an implementation (i.e., the more internal invariants it possesses) - the higher its amortized
complexity of push and pop operations.
This library implements different algorithms using a single class: priority_queue. Instantiating the Tag template parameter,
"selects" the implementation:
1. Instantiating Tag =binary_heap_tag creates a binary heap of the form in represented in the graphic with labels A1
or A2. The former is internally selected by priority_queue if Value_Type is instantiated by a primitive type (e.g., an int);

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the latter is internally selected for all other types (e.g., std::string). This implementations is relatively unstructured,
and so has good push and pop performance; it is the "best-in-kind" for primitive types, e.g., ints. Conversely, it has high
worst-case performance, and can support only linear-time modify and erase operations.
2. Instantiating Tag =pairing_heap_tag creates a pairing heap of the form in represented by label B in the graphic
above. This implementations too is relatively unstructured, and so has good push and pop performance; it is the "bestin-kind" for non-primitive types, e.g., std:strings. It also has very good worst-case push and join performance
(O(1)), but has high worst-case pop complexity.
3. Instantiating Tag =binomial_heap_tag creates a binomial heap of the form repsented by label B in the graphic
above. This implementations is more structured than a pairing heap, and so has worse push and pop performance.
Conversely, it has sub-linear worst-case bounds for pop, e.g., and so it might be preferred in cases where responsiveness
is important.
4. Instantiating Tag =rc_binomial_heap_tag creates a binomial heap of the form represented in label B above, accompanied by a redundant counter which governs the trees. This implementations is therefore more structured than a
binomial heap, and so has worse push and pop performance. Conversely, it guarantees O(1) push complexity, and so it
might be preferred in cases where the responsiveness of a binomial heap is insufficient.
5. Instantiating Tag =thin_heap_tag creates a thin heap of the form represented by the label B in the graphic above.
This implementations too is more structured than a pairing heap, and so has worse push and pop performance. Conversely, it has better worst-case and identical amortized complexities than a Fibonacci heap, and so might be more appropriate for some graph algorithms.
Of course, one can use any order-preserving associative container as a priority queue, as in the graphic above label C, possibly
by creating an adapter class over the associative container (much as std::priority_queue can adapt std::vector).
This has the advantage that no cross-referencing is necessary at all; the priority queue itself is an associative container. Most
associative containers are too structured to compete with priority queues in terms of push and pop performance.
22.3.2.5.2.3

Traits

It would be nice if all priority queues could share exactly the same behavior regardless of implementation. Sadly, this is not
possible. Just one for instance is in join operations: joining two binary heaps might throw an exception (not corrupt any of the
heaps on which it operates), but joining two pairing heaps is exception free.
Tags and traits are very useful for manipulating generic types. __gnu_pbds::priority_queue publicly defines conta
iner_category as one of the tags. Given any container Cntnr, the tag of the underlying data structure can be found via
typename Cntnr::container_category; this is one of the possible tags shown in the graphic below.

Figure 22.33: Priority-Queue Data-Structure Tags.
Additionally, a traits mechanism can be used to query a container type for its attributes. Given any container Cntnr, then

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__gnu_pbds::container_traits

is a traits class identifying the properties of the container.
To find if a container might throw if two of its objects are joined, one can use
container_traits::split_join_can_throw

Different priority-queue implementations have different invalidation guarantees. This is especially important, since there is no
way to access an arbitrary value of priority queues except for iterators. Similarly to associative containers, one can use
container_traits::invalidation_guarantee

to get the invalidation guarantee type of a priority queue.
It is easy to understand from the graphic above, what container_traits::invalidation_guarantee will
be for different implementations. All implementations of type represented by label B have point_invalidation_guar
antee: the container can freely internally reorganize the nodes - range-type iterators are invalidated, but point-type iterators
are always valid. Implementations of type represented by labels A1 and A2 have basic_invalidation_guarantee: the
container can freely internally reallocate the array - both point-type and range-type iterators might be invalidated.
This has major implications, and constitutes a good reason to avoid using binary heaps. A binary heap can perform modify or
erase efficiently given a valid point-type iterator. However, in order to supply it with a valid point-type iterator, one needs to
iterate (linearly) over all values, then supply the relevant iterator (recall that a range-type iterator can always be converted to a
point-type iterator). This means that if the number of modify or erase operations is non-negligible (say super-logarithmic in
the total sequence of operations) - binary heaps will perform badly.

22.4

Testing

22.4.1

Regression

The library contains a single comprehensive regression test. For a given container type in this library, the test creates an object of
the container type and an object of the corresponding standard type (e.g., std::set). It then performs a random sequence of
methods with random arguments (e.g., inserts, erases, and so forth) on both objects. At each operation, the test checks the return
value of the method, and optionally both compares this library’s object with the standard’s object as well as performing other
consistency checks on this library’s object (e.g., order preservation, when applicable, or node invariants, when applicable).
Additionally, the test integrally checks exception safety and resource leaks. This is done as follows. A special allocator type,
written for the purpose of the test, both randomly throws an exceptions when allocations are performed, and tracks allocations
and de-allocations. The exceptions thrown at allocations simulate memory-allocation failures; the tracking mechanism checks
for memory-related bugs (e.g., resource leaks and multiple de-allocations). Both this library’s containers and the containers’
value-types are configured to use this allocator.
For granularity, the test is split into the several sources, each checking only some containers.
For more details, consult the files in testsuite/ext/pb_ds/regression.

22.4.2

Performance

22.4.2.1

Hash-Based

22.4.2.1.1
22.4.2.1.1.1

Text find
Description

This test inserts a number of values with keys from an arbitrary text ([98]) into a container, then performs a series of finds using
find . It measures the average time for find as a function of the number of values inserted.

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It uses the test file: performance/ext/pb_ds/text_find_timing_test.cc
And uses the data file: filethirty_years_among_the_dead_preproc.txt
The test checks the effect of different range-hashing functions, trigger policies, and cache-hashing policies.
22.4.2.1.1.2

Results

The graphic below show the results for the native and collision-chaining hash types the function applied being a text find timing
test using find.

Average time (sec.)

5.33e-08
4.26e-08
3.20e-08
2.13e-08
1.07e-08
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

cc_hash_mod_prime_nea_lc_1div8_1div1_nsth_map
cc_hash_mask_exp_nea_lc_1div8_1div1_nsth_map
cc_hash_mask_exp_nea_lc_1div8_1div2_sth_map
cc_hash_mask_exp_nea_lc_1div8_1div2_nsth_map

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_map_ncah
std::tr1::
cache_hash_c
unordered_map
ode
cc_hash_mod_prime_1div1_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

Details

Parameter

Details

false
direct_mod_ran
ge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/1

cc_hash_mask_exp_1div2_sth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

direct_mask_ra
nge_hashing
hash_standard_
resize_policy

Size_Policy

hash_exponenti
al_size_policy

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Type

Parameter

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Details

Parameter

Details

Trigger_Policy

hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

cc_hash_mask_exp_1div1_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

direct_mask_ra
nge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

hash_exponenti
al_size_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/1

cc_hash_mask_exp_1div2_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

direct_mask_ra
nge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

22.4.2.1.1.3

hash_exponenti
al_size_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

Observations

In this setting, the range-hashing scheme affects performance more than other policies. As the results show, containers using
mod-based range-hashing (including the native hash-based container, which is currently hard-wired to this scheme) have lower
performance than those using mask-based range-hashing. A modulo-based range-hashing scheme’s main benefit is that it takes
into account all hash-value bits. Standard string hash-functions are designed to create hash values that are nearly-uniform as is
([77]).
Trigger policies, i.e. the load-checks constants, affect performance to a lesser extent.
Perhaps surprisingly, storing the hash value alongside each entry affects performance only marginally, at least in this library’s
implementation. (Unfortunately, it was not possible to run the tests with std::tr1::unordered_map ’s cache_hash_c
ode =true , as it appeared to malfuntion.)
22.4.2.1.2
22.4.2.1.2.1

Integer find
Description

This test inserts a number of values with uniform integer keys into a container, then performs a series of finds using find. It
measures the average time for find as a function of the number of values inserted.
It uses the test file: performance/ext/pb_ds/random_int_find_timing.cc
The test checks the effect of different underlying hash-tables, range-hashing functions, and trigger policies.
22.4.2.1.2.2

Results

There are two sets of results for this type, one for collision-chaining hashes, and one for general-probe hashes.
The first graphic below shows the results for the native and collision-chaining hash types. The function applied being a random
integer timing test using find.

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Average time (sec.)

1.90e-08
1.52e-08
1.14e-08
7.58e-09
3.79e-09
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_hash_map_ncah
cc_hash_mod_prime_nea_lc_1div8_1div1_nsth_map
cc_hash_mod_prime_nea_lc_1div8_1div2_nsth_map
cc_hash_mask_exp_nea_lc_1div8_1div1_nsth_map
cc_hash_mask_exp_nea_lc_1div8_1div2_nsth_map

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_map_ncah
std::tr1::
cache_hash_c
unordered_map
ode
cc_hash_mod_prime_1div1_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

Details

Parameter

Details

false
direct_mod_ran
ge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/1

cc_hash_mod_prime_1div2_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

direct_mod_ran
ge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

cc_hash_mask_exp_1div1_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

direct_mask_ra
nge_hashing
hash_standard_
resize_policy

Size_Policy

hash_exponenti
al_size_policy

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Type

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Parameter

Details

Parameter

Details

Trigger_Policy

hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/1

cc_hash_mask_exp_1div2_nsth_map
cc_hash_table

direct_mask_ra
nge_hashing

Comb_Hash_Fn
Resize_Policy

hash_exponenti
al_size_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

Size_Policy

hash_standard_
resize_policy

Trigger_Policy

And the second graphic shows the results for the native and general-probe hash types. The function applied being a random
integer timing test using find.

Average time (sec.)

3.06e-08
2.45e-08
1.84e-08
1.22e-08
6.12e-09
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

gp_hash_mod_quadp_prime_nea_lc_1div8_1div2_nsth_map
n_hash_map_ncah
gp_hash_mask_linp_exp_nea_lc_1div8_1div2_nsth_map

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_map_ncah
std::tr1::
cache_hash_c
unordered_map
ode
gp_hash_mod_quadp_prime_1div2_nsth_map
gp_hash_table

Comb_Hash_Fn
Probe_Fn

Details

false
direct_mod_ran
ge_hashing
quadratic_prob
e_fn

Parameter

Details

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Type

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Parameter

Details

Parameter

Resize_Policy

hash_standard_
resize_policy

Size_Policy

Trigger_Policy

Details
hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

gp_hash_mask_linp_exp_1div2_nsth_map
gp_hash_table

Comb_Hash_Fn
Probe_Fn
Resize_Policy

direct_mask_ra
nge_hashing
linear_probe
_fn
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

22.4.2.1.2.3

hash_exponenti
al_size_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

Observations

In this setting, the choice of underlying hash-table affects performance most, then the range-hashing scheme and, only finally,
other policies.
When comparing probing and chaining containers, it is apparent that the probing containers are less efficient than the collisionchaining containers ( std::tr1::unordered_map uses collision-chaining) in this case.
Hash-Based Integer Subscript Insert Timing Test shows a different case, where the situation is reversed;
Within each type of hash-table, the range-hashing scheme affects performance more than other policies; Hash-Based Text find
Find Timing Test also shows this. In the above graphics should be noted that std::tr1::unordered_map are hard-wired
currently to mod-based schemes.
22.4.2.1.3
22.4.2.1.3.1

Integer Subscript find
Description

This test inserts a number of values with uniform integer keys into a container, then performs a series of finds using operato
r[]. It measures the average time for operator[] as a function of the number of values inserted.
It uses the test file: performance/ext/pb_ds/random_int_subscript_find_timing.cc
The test checks the effect of different underlying hash-tables, range-hashing functions, and trigger policies.
22.4.2.1.3.2

Results

There are two sets of results for this type, one for collision-chaining hashes, and one for general-probe hashes.
The first graphic below shows the results for the native and collision-chaining hash types, using as the function applied an integer
subscript timing test with find.

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Average time (sec.)

1.84e-08
1.47e-08
1.11e-08
7.37e-09
3.68e-09
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_hash_map_ncah
cc_hash_mod_prime_nea_lc_1div8_1div1_nsth_map
cc_hash_mod_prime_nea_lc_1div8_1div2_nsth_map
cc_hash_mask_exp_nea_lc_1div8_1div1_nsth_map
cc_hash_mask_exp_nea_lc_1div8_1div2_nsth_map

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_map_ncah
std::tr1::
cache_hash_c
unordered_map
ode
cc_hash_mod_prime_1div1_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

Details

Parameter

Details

false
direct_mod_ran
ge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/1

cc_hash_mod_prime_1div2_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

direct_mod_ran
ge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

cc_hash_mask_exp_1div1_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

direct_mask_ra
nge_hashing
hash_standard_
resize_policy

Size_Policy

hash_exponenti
al_size_policy

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Type

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Parameter

Details

Parameter

Details

Trigger_Policy

hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/1

cc_hash_mask_exp_1div2_nsth_map
cc_hash_table

direct_mask_ra
nge_hashing

Comb_Hash_Fn
Resize_Policy

hash_exponenti
al_size_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

Size_Policy

hash_standard_
resize_policy

Trigger_Policy

And the second graphic shows the results for the native and general-probe hash types. The function applied being a random
integer timing test using find.

Average time (sec.)

2.98e-08
2.38e-08
1.79e-08
1.19e-08
5.96e-09
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

gp_hash_mod_quadp_prime_nea_lc_1div8_1div2_nsth_map
n_hash_map_ncah
gp_hash_mask_linp_exp_nea_lc_1div8_1div2_nsth_map

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_map_ncah
std::tr1::
cache_hash_c
unordered_map
ode
gp_hash_mod_quadp_prime_1div2_nsth_map
gp_hash_table

Comb_Hash_Fn
Probe_Fn

Details

false
direct_mod_ran
ge_hashing
quadratic_prob
e_fn

Parameter

Details

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Name/Instantiating
Type

222 / 399

Parameter

Details

Parameter

Resize_Policy

hash_standard_
resize_policy

Size_Policy

Trigger_Policy

Details
hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

gp_hash_mask_linp_exp_1div2_nsth_map
gp_hash_table

Comb_Hash_Fn
Probe_Fn
Resize_Policy

direct_mask_ra
nge_hashing
linear_probe
_fn
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

22.4.2.1.3.3

hash_exponenti
al_size_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

Observations

This test shows similar results to Hash-Based Integer find Find Timing test.
22.4.2.1.4
22.4.2.1.4.1

Integer Subscript insert
Description

This test inserts a number of values with uniform i.i.d. integer keys into a container, using operator[]. It measures the
average time for operator[] as a function of the number of values inserted.
It uses the test file: performance/ext/pb_ds/random_int_subscript_insert_timing.cc
The test checks the effect of different underlying hash-tables.
22.4.2.1.4.2

Results

There are two sets of results for this type, one for collision-chaining hashes, and one for general-probe hashes.
The first graphic below shows the results for the native and collision-chaining hash types, using as the function applied an integer
subscript timing test with insert.

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Average time (sec.)

1.36e-07
1.09e-07
8.18e-08
5.45e-08
2.73e-08
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

cc_hash_mod_prime_nea_lc_1div8_1div2_nsth_map
n_hash_map_ncah
cc_hash_mod_prime_nea_lc_1div8_1div1_nsth_map
cc_hash_mask_exp_nea_lc_1div8_1div2_nsth_map
cc_hash_mask_exp_nea_lc_1div8_1div1_nsth_map

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_map_ncah
std::tr1::
cache_hash_c
unordered_map
ode
cc_hash_mod_prime_1div1_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

Details

Parameter

Details

false
direct_mod_ran
ge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/1

cc_hash_mod_prime_1div2_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

direct_mod_ran
ge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

cc_hash_mask_exp_1div1_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

direct_mask_ra
nge_hashing
hash_standard_
resize_policy

Size_Policy

hash_exponenti
al_size_policy

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Type

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Parameter

Details

Parameter

Details

Trigger_Policy

hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/1

cc_hash_mask_exp_1div2_nsth_map
cc_hash_table

direct_mask_ra
nge_hashing

Comb_Hash_Fn
Resize_Policy

hash_exponenti
al_size_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

Size_Policy

hash_standard_
resize_policy

Trigger_Policy

And the second graphic shows the results for the native and general-probe hash types. The function applied being a random
integer timing test using find.

Average time (sec.)

1.59e-07
1.27e-07
9.54e-08
6.36e-08
3.18e-08
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_hash_map_ncah
gp_hash_mod_quadp_prime_nea_lc_1div8_1div2_nsth_map
gp_hash_mask_linp_exp_nea_lc_1div8_1div2_nsth_map

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_map_ncah
std::tr1::
cache_hash_c
unordered_map
ode
gp_hash_mod_quadp_prime_1div2_nsth_map
gp_hash_table

Comb_Hash_Fn
Probe_Fn

Details

false
direct_mod_ran
ge_hashing
quadratic_prob
e_fn

Parameter

Details

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Name/Instantiating
Type

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Parameter

Details

Parameter

Resize_Policy

hash_standard_
resize_policy

Size_Policy

Trigger_Policy

Details
hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

gp_hash_mask_linp_exp_1div2_nsth_map
gp_hash_table

Comb_Hash_Fn
Probe_Fn
Resize_Policy

direct_mask_ra
nge_hashing
linear_probe
_fn
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

22.4.2.1.4.3

hash_exponenti
al_size_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

Observations

In this setting, as in Hash-Based Text find Find Timing test and Hash-Based Integer find Find Timing test , the choice of
underlying hash-table underlying hash-table affects performance most, then the range-hashing scheme, and finally any other
policies.
There are some differences, however:
1. In this setting, probing tables function sometimes more efficiently than collision-chaining tables. This is explained shortly.
2. The performance graphs have a "saw-tooth" shape. The average insert time rises and falls. As values are inserted into
the container, the load factor grows larger. Eventually, a resize occurs. The reallocations and rehashing are relatively
expensive. After this, the load factor is smaller than before.
Collision-chaining containers use indirection for greater flexibility; probing containers store values contiguously, in an array (see
Figure Motivation::Different underlying data structures A and B, respectively). It follows that for simple data types, probing
containers access their allocator less frequently than collision-chaining containers, (although they still have less efficient probing
sequences). This explains why some probing containers fare better than collision-chaining containers in this case.
Within each type of hash-table, the range-hashing scheme affects performance more than other policies. This is similar to the
situation in Hash-Based Text find Find Timing Test and Hash-Based Integer find Find Timing Test. Unsurprisingly, however,
containers with lower α max perform worse in this case, since more re-hashes are performed.
22.4.2.1.5
22.4.2.1.5.1

Integer find with Skewed-Distribution
Description

This test inserts a number of values with a markedly non-uniform integer keys into a container, then performs a series of finds
using find. It measures the average time for find as a function of the number of values in the containers. The keys are
generated as follows. First, a uniform integer is created. Then it is then shifted left 8 bits.
It uses the test file: performance/ext/pb_ds/hash_zlob_random_int_find_timing.cc
The test checks the effect of different range-hashing functions and trigger policies.

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Results

Average time (sec.)

The graphic below show the results for the native, collision-chaining, and general-probing hash types.

2.61e-07
1.96e-07
1.31e-07
6.53e-08
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

cc_hash_mask_exp_nea_lc_1div8_1div1_nsth_map
gp_hash_mod_quadp_prime_nea_lc_1div8_1div2_nsth_map
n_hash_map_ncah
cc_hash_mod_prime_nea_lc_1div8_1div1_nsth_map

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_map_ncah
std::tr1::
cache_hash_c
unordered_map
ode
cc_hash_mod_prime_1div1_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

Details

Parameter

Details

false
direct_mod_ran
ge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/1

cc_hash_mask_exp_1div1_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

direct_mask_ra
nge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy
gp_hash_mod_quadp_prime_1div2_nsth_map
gp_hash_table

Comb_Hash_Fn

direct_mod_ran
ge_hashing

hash_exponenti
al_size_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/1

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Type

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Parameter

Details

Probe_Fn

quadratic_prob
e_fn

Resize_Policy

hash_standard_
resize_policy

Parameter

Size_Policy

Trigger_Policy

22.4.2.1.5.3

Details

hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

Observations

In this setting, the distribution of keys is so skewed that the underlying hash-table type affects performance marginally. (This
is in contrast with Hash-Based Text find Find Timing Test, Hash-Based Integer find Find Timing Test, Hash-Based Integer
Subscript Find Timing Test and Hash-Based Integer Subscript Insert Timing Test.)
The range-hashing scheme affects performance dramatically. A mask-based range-hashing scheme effectively maps all values
into the same bucket. Access degenerates into a search within an unordered linked-list. In the graphic above, it should be noted
that std::tr1::unordered_map is hard-wired currently to mod-based and mask-based schemes, respectively.
When observing the settings of this test, it is apparent that the keys’ distribution is far from natural. One might ask if the test
is not contrived to show that, in some cases, mod-based range hashing does better than mask-based range hashing. This is, in
fact just the case. A more natural case in which mod-based range hashing is better was not encountered. Thus the inescapable
conclusion: real-life key distributions are handled better with an appropriate hash function and a mask-based range-hashing
function. (pb_ds/example/hash_shift_mask.cc shows an example of handling this a-priori known skewed distribution
with a mask-based range-hashing function). If hash performance is bad, a χ 2 test can be used to check how to transform it into a
more uniform distribution.
For this reason, this library’s default range-hashing function is mask-based.
22.4.2.1.6
22.4.2.1.6.1

Erase Memory Use
Description

This test inserts a number of uniform integer keys into a container, then erases all keys except one. It measures the final size of
the container.
It uses the test file: performance/ext/pb_ds/hash_random_int_erase_mem_usage.cc
The test checks how containers adjust internally as their logical size decreases.
22.4.2.1.6.2

Results

The graphic below show the results for the native, collision-chaining, and general-probing hash types.

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Memory (bytes)

2.28e+04
1.95e+04
1.63e+04
1.30e+04
9.75e+03
6.50e+03
3.25e+03
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_hash_set_ncah
cc_hash_mod_prime_nea_lc_1div8_1div1_nsth_set
cc_hash_mask_exp_nea_lc_1div8_1div2_nsth_set
gp_hash_mask_linp_exp_nea_lc_1div8_1div2_nsth_set

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_map_ncah
std::tr1::
cache_hash_c
unordered_map
ode
cc_hash_mod_prime_1div1_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

Details

Parameter

Details

false
direct_mod_ran
ge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

hash_prime_siz
e_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/1

cc_hash_mask_exp_1div2_nsth_map
cc_hash_table

Comb_Hash_Fn
Resize_Policy

direct_mask_ra
nge_hashing
hash_standard_
resize_policy

Size_Policy

Trigger_Policy

hash_exponenti
al_size_policy
hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

gp_hash_mask_linp_exp_1div2_nsth_set
gp_hash_table

Comb_Hash_Fn
Probe_Fn
Resize_Policy

direct_mask_ra
nge_hashing
linear_probe
_fn
hash_standard_
resize_policy

Size_Policy

hash_exponenti
al_size_policy

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Name/Instantiating
Type

22.4.2.1.6.3

229 / 399

Parameter

Details

Parameter

Details

Trigger_Policy

hash_load_chec
k_resize_trig
ger with α min = 1/8
and α max = 1/2

Observations

The standard’s hash-based containers act very differently than trees in this respect. When erasing numerous keys from an
standard associative-container, the resulting memory user varies greatly depending on whether the container is tree-based or
hash-based. This is a fundamental consequence of the standard’s interface for associative containers, and it is not due to a
specific implementation.
22.4.2.2

Branch-Based

22.4.2.2.1
22.4.2.2.1.1

Text insert
Description

This test inserts a number of values with keys from an arbitrary text ([ wickland96thirty ]) into a container using insert . It
measures the average time for insert as a function of the number of values inserted.
The test checks the effect of different underlying data structures.
It uses the test file: performance/ext/pb_ds/tree_text_insert_timing.cc
22.4.2.2.1.2

Results

The three graphics below show the results for the native tree and this library’s node-based trees, the native tree and this library’s
vector-based trees, and the native tree and this library’s PATRICIA-trie, respectively.
The graphic immediately below shows the results for the native tree type and several node-based tree types.

Average time (sec.)

4.08e-07
3.27e-07
2.45e-07
1.63e-07
8.16e-08
0.00e+00
2200

2000

1800

1600

1400

splay_tree_map
n_map
rb_tree_map

1200

1000

800

600

400

200

0

Size

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The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_map
std::map
splay_tree_map
tree
rb_tree_map
tree

Parameter

Details

Tag
Node_update

splay_tree_tag
null_node_update

Tag
Node_update

rb_tree_tag
null_node_update

The graphic below shows the results for the native tree type and a vector-based tree type.

Average time (sec.)

2.45e-06
1.96e-06
1.47e-06
9.78e-07
4.89e-07
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

ov_tree_map
n_map

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_map
std::map
ov_tree_map
tree

Parameter

Details

Tag
Node_update

ov_tree_tag
null_node_update

The graphic below shows the results for the native tree type and a PATRICIA trie type.

The GNU C++ Library Manual

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Average time (sec.)

4.38e-07
3.50e-07
2.63e-07
1.75e-07
8.75e-08
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

pat_trie_map
n_map

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_map
std::map
pat_trie_map
tree

22.4.2.2.1.3

Parameter

Details

Tag
Node_update

pat_trie_tag
null_node_update

Observations

Observing the first graphic implies that for this setting, a splay tree (tree with Tag = splay_tree_tag) does not do well.
See also the Branch-Based Text find Find Timing Test. The two red-black trees perform better.
Observing the second graphic, an ordered-vector tree (tree with Tag = ov_tree_tag) performs abysmally. Inserting into
this type of tree has linear complexity [ austern00noset].
Observing the third and last graphic, A PATRICIA trie (trie with Tag = pat_trie_tag) has abysmal performance, as
well. This is not that surprising, since a large-fan-out PATRICIA trie works like a hash table with collisions resolved by a subtrie. Each time a collision is encountered, a new "hash-table" is built A large fan-out PATRICIA trie, however, doe does well in
look-ups (see Branch-Based Text find Find Timing Test). It may be beneficial in semi-static settings.
22.4.2.2.2
22.4.2.2.2.1

Text find
Description

This test inserts a number of values with keys from an arbitrary text ([wickland96thirty]) into a container, then performs a series
of finds using find. It measures the average time for find as a function of the number of values inserted.
It uses the test file: performance/ext/pb_ds/text_find_timing.cc
The test checks the effect of different underlying data structures.

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Results

The graphic immediately below shows the results for the native tree type and several other tree types.

Average time (sec.)

4.23e-07
3.39e-07
2.54e-07
1.69e-07
8.47e-08
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

splay_tree_map
n_map
ov_tree_map
rb_tree_map
pat_trie_map

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_map
std::map
splay_tree_map
tree
rb_tree_map
tree
ov_tree_map
tree
pat_trie_map
tree

22.4.2.2.2.3

Parameter

Details

Tag
Node_Update

splay_tree_tag
null_node_update

Tag
Node_Update

rb_tree_tag
null_node_update

Tag
Node_Update

ov_tree_tag
null_node_update

Tag
Node_Update

pat_trie_tag
null_node_update

Observations

For this setting, a splay tree (tree with Tag = splay_tree_tag) does not do well. This is possibly due to two reasons:
1. A splay tree is not guaranteed to be balanced [motwani95random]. If a splay tree contains n nodes, its average root-leaf
path can be m >> log(n).

The GNU C++ Library Manual

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2. Assume a specific root-leaf search path has length m, and the search-target node has distance m’ from the root. A red-black
tree will require m + 1 comparisons to find the required node; a splay tree will require 2 m’ comparisons. A splay tree,
consequently, can perform many more comparisons than a red-black tree.
An ordered-vector tree (tree with Tag = ov_tree_tag), a red-black tree (tree with Tag = rb_tree_tag), and the
native red-black tree all share approximately the same performance.
An ordered-vector tree is slightly slower than red-black trees, since it requires, in order to find a key, more math operations than
they do. Conversely, an ordered-vector tree requires far lower space than the others. ([austern00noset], however, seems to have
an implementation that is also faster than a red-black tree).
A PATRICIA trie (trie with Tag = pat_trie_tag) has good look-up performance, due to its large fan-out in this case. In
this setting, a PATRICIA trie has look-up performance comparable to a hash table (see Hash-Based Text find Timing Test),
but it is order preserving. This is not that surprising, since a large-fan-out PATRICIA trie works like a hash table with collisions
resolved by a sub-trie. A large-fan-out PATRICIA trie does not do well on modifications (see Tree-Based and Trie-Based Text
Insert Timing Test). Therefore, it is possibly beneficial in semi-static settings.
22.4.2.2.3
22.4.2.2.3.1

Text find with Locality-of-Reference
Description

This test inserts a number of values with keys from an arbitrary text ([ wickland96thirty ]) into a container, then performs a series
of finds using find. It is different than Tree-Based and Trie-Based Text find Find Timing Test in the sequence of finds it
performs: this test performs multiple finds on the same key before moving on to the next key. It measures the average time for
find as a function of the number of values inserted.
It uses the test file: performance/ext/pb_ds/tree_text_lor_find_timing.cc
The test checks the effect of different underlying data structures in a locality-of-reference setting.
22.4.2.2.3.2

Results

The graphic immediately below shows the results for the native tree type and several other tree types.

Average time (sec.)

2.29e-07
1.83e-07
1.37e-07
9.16e-08
4.58e-08
0.00e+00
2200

2000

1800

1600

1400

ov_tree_map
n_map
rb_tree_map
splay_tree_map

1200

1000

800

600

400

200

0

Size

The GNU C++ Library Manual

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The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_map
std::map
splay_tree_map
tree
rb_tree_map
tree
ov_tree_map
tree
pat_trie_map
tree

22.4.2.2.3.3

Parameter

Details

Tag
Node_Update

splay_tree_tag
null_node_update

Tag
Node_Update

rb_tree_tag
null_node_update

Tag
Node_Update

ov_tree_tag
null_node_update

Tag
Node_Update

pat_trie_tag
null_node_update

Observations

For this setting, an ordered-vector tree (tree with Tag = ov_tree_tag), a red-black tree (tree with Tag = rb_tree_
tag), and the native red-black tree all share approximately the same performance.
A splay tree (tree with Tag = splay_tree_tag) does much better, since each (successful) find "bubbles" the corresponding
node to the root of the tree.
22.4.2.2.4
22.4.2.2.4.1

split and join
Description

This test a container, inserts into a number of values, splits the container at the median, and joins the two containers. (If the
containers are one of this library’s trees, it splits and joins with the split and join method; otherwise, it uses the erase and
insert methods.) It measures the time for splitting and joining the containers as a function of the number of values inserted.
It uses the test file: performance/ext/pb_ds/tree_split_join_timing.cc
The test checks the performance difference of join as opposed to a sequence of insert operations; by implication, this test
checks the most efficient way to erase a sub-sequence from a tree-like-based container, since this can always be performed by a
small sequence of splits and joins.
22.4.2.2.4.2

Results

The graphic immediately below shows the results for the native tree type and several other tree types.

The GNU C++ Library Manual

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Average time (sec.)

2.36e-04
1.89e-04
1.41e-04
9.43e-05
4.72e-05
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_set
splay_tree_set
rb_tree_set
ov_tree_set

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_set
std::set
splay_tree_set
tree
rb_tree_set
tree
ov_tree_set
tree
pat_trie_map
tree

22.4.2.2.4.3

Parameter

Details

Tag
Node_Update

splay_tree_tag
null_node_update

Tag
Node_Update

rb_tree_tag
null_node_update

Tag
Node_Update

ov_tree_tag
null_node_update

Tag
Node_Update

pat_trie_tag
null_node_update

Observations

In this test, the native red-black trees must be split and joined externally, through a sequence of erase and insert operations.
This is clearly super-linear, and it is not that surprising that the cost is high.
This library’s tree-based containers use in this test the split and join methods, which have lower complexity: the join
method of a splay tree (tree with Tag = splay_tree_tag) is quadratic in the length of the longest root-leaf path, and
linear in the total number of elements; the join method of a red-black tree (tree with Tag = rb_tree_tag) or an orderedvector tree (tree with Tag = ov_tree_tag) is linear in the number of elements.
Asides from orders of growth, this library’s trees access their allocator very little in these operations, and some of them do not
access it at all. This leads to lower constants in their complexity, and, for some containers, to exception-free splits and joins
(which can be determined via container_traits).

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It is important to note that split and join are not esoteric methods - they are the most efficient means of erasing a contiguous
range of values from a tree based container.
22.4.2.2.5
22.4.2.2.5.1

Order-Statistics
Description

This test creates a container, inserts random integers into the the container, and then checks the order-statistics of the container’s
values. (If the container is one of this library’s trees, it does this with the order_of_key method of tree_order_stati
stics_node_update ; otherwise, it uses the find method and std::distance.) It measures the average time for such
queries as a function of the number of values inserted.
It uses the test file: performance/ext/pb_ds/tree_order_statistics_timing.cc
The test checks the performance difference of policies based on node-invariant as opposed to a external functions.
22.4.2.2.5.2

Results

The graphic immediately below shows the results for the native tree type and several other tree types.

Average time (sec.)

9.33e-06
7.47e-06
5.60e-06
3.73e-06
1.87e-06
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_set
splay_tree_ost_set
rb_tree_ost_set

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_set
std::set
splay_tree_ost_set
tree

Parameter

Details

Tag

splay_tree_tag
tree_order_statistics_nod
e_update

Node_Update
rb_tree_ost_set
tree

Tag
Node_Update

rb_tree_tag
tree_order_statistics_nod
e_update

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Observations

In this test, the native red-black tree can support order-statistics queries only externally, by performing a find (alternatively,
lower_bound or upper_bound ) and then using std::distance . This is clearly linear, and it is not that surprising that
the cost is high.
This library’s tree-based containers use in this test the order_of_key method of tree_order_statistics_node_up
date. This method has only linear complexity in the length of the root-node path. Unfortunately, the average path of a splay
tree (tree with Tag = splay_tree_tag ) can be higher than logarithmic; the longest path of a red-black tree (tree with
Tag = rb_tree_tag ) is logarithmic in the number of elements. Consequently, the splay tree has worse performance than
the red-black tree.
22.4.2.3

Multimap

22.4.2.3.1
22.4.2.3.1.1

Text find with Small Secondary-to-Primary Key Ratios
Description

This test inserts a number of pairs into a container. The first item of each pair is a string from an arbitrary text [wickland96thirty],
and the second is a uniform i.i.d.integer. The container is a "multimap" - it considers the first member of each pair as a primary
key, and the second member of each pair as a secondary key (see Motivation::Associative Containers::Alternative to Multiple
Equivalent Keys). There are 400 distinct primary keys, and the ratio of secondary keys to primary keys ranges from 1 to 5.
The test measures the average find-time as a function of the number of values inserted. For this library’s containers, it finds the
secondary key from a container obtained from finding a primary key. For the native multimaps, it searches a range obtained using
std::equal_range on a primary key.
It uses the test file: performance/ext/pb_ds/multimap_text_find_timing_small.cc
The test checks the find-time scalability of different "multimap" designs.
22.4.2.3.1.2

Results

The graphic below show the results for "multimaps" which use a tree-based container for primary keys.

The GNU C++ Library Manual

238 / 399

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_mmap
std::
multimap
rb_tree_mmap_lu_mtf_set
tree

Tag
Node_Upd
ate
Mapped

Details

Parameter

Details

Update_Po
licy

lu_move_t
o_front_p
olicy

Comb_Hash
_Fn

direct_ma
sk_range_
hashing

rb_tree_
tag
null_node
_update
list_upd
ate

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
rb_tree_
Tag
tree
tag
Node_Upd
null_node
ate
_update
Mapped

cc_hash_t
able

Parameter

Details

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type

239 / 399

Details

Parameter

Resize_Po
licy

Details

hash_stan
dard_resi
ze_policy

Parameter
Size_Pol
icy

Trigger_P
olicy

Details
hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

The graphic below show the results for "multimaps" which use a hash-based container for primary keys.

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_mmap
std::tr1:
:
unordered
_multimap

Details

Parameter

Details

Parameter

Details

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type
rb_tree_mmap_lu_mtf_set
cc_hash_
table

Comb_Hash
_Fn

Resize_Po
licy

240 / 399

Details

Parameter

Parameter

Details

direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

Mapped

Details

list_upd
ate

Update_Po
licy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2
lu_move_t
o_front_p
olicy

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
direct_ma
Comb_Hash
sk_range_
cc_hash_
_Fn
hashing
table
Resize_Po
licy

hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

Mapped

cc_hash_t
able

Comb_Hash
_Fn

Resize_Po
licy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2
direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

22.4.2.3.1.3

Observations

See Observations::Mapping-Semantics Considerations.

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

The GNU C++ Library Manual

22.4.2.3.2
22.4.2.3.2.1

241 / 399

Text find with Large Secondary-to-Primary Key Ratios
Description

This test inserts a number of pairs into a container. The first item of each pair is a string from an arbitrary text [wickland96thirty],
and the second is a uniform integer. The container is a "multimap" - it considers the first member of each pair as a primary key,
and the second member of each pair as a secondary key. There are 400 distinct primary keys, and the ratio of secondary keys to
primary keys ranges from 1 to 5.
The test measures the average find-time as a function of the number of values inserted. For this library’s containers, it finds the
secondary key from a container obtained from finding a primary key. For the native multimaps, it searches a range obtained using
std::equal_range on a primary key.
It uses the test file: performance/ext/pb_ds/multimap_text_find_timing_large.cc
The test checks the find-time scalability of different "multimap" designs.
22.4.2.3.2.2

Results

The graphic below show the results for "multimaps" which use a tree-based container for primary keys.

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type
n_mmap
std::
multimap
rb_tree_mmap_lu_mtf_set
tree

Tag
Node_Upd
ate
Mapped

242 / 399

Details

Parameter

Details

Update_Po
licy

lu_move_t
o_front_p
olicy

Comb_Hash
_Fn

direct_ma
sk_range_
hashing

Parameter

Details

rb_tree_
tag
null_node
_update
list_upd
ate

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
rb_tree_
Tag
tree
tag
Node_Upd
null_node
ate
_update
Mapped

cc_hash_t
able

Resize_Po
licy

hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

The graphic below show the results for "multimaps" which use a hash-based container for primary keys.

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

The GNU C++ Library Manual

243 / 399

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_mmap
std::tr1:
:
unordered
_multimap
rb_tree_mmap_lu_mtf_set
cc_hash_
table

Comb_Hash
_Fn

Resize_Po
licy

Details

Parameter

Details

direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

Parameter

Details

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type
Mapped

244 / 399

Details

Parameter

Details

list_upd
ate

Update_Po
licy

lu_move_t
o_front_p
olicy

Parameter

Details

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
direct_ma
Comb_Hash
sk_range_
cc_hash_
_Fn
hashing
table
Resize_Po
licy

hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

Mapped

cc_hash_t
able

Comb_Hash
_Fn

Resize_Po
licy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2
direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

22.4.2.3.2.3

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

Observations

See Observations::Mapping-Semantics Considerations.
22.4.2.3.3
22.4.2.3.3.1

Text insert with Small Secondary-to-Primary Key Ratios
Description

This test inserts a number of pairs into a container. The first item of each pair is a string from an arbitrary text [wickland96thirty],
and the second is a uniform integer. The container is a "multimap" - it considers the first member of each pair as a primary key,
and the second member of each pair as a secondary key. There are 400 distinct primary keys, and the ratio of secondary keys to
primary keys ranges from 1 to 5.
The test measures the average insert-time as a function of the number of values inserted. For this library’s containers, it inserts a
primary key into the primary associative container, then a secondary key into the secondary associative container. For the native
multimaps, it obtains a range using std::equal_range, and inserts a value only if it was not contained already.
It uses the test file: performance/ext/pb_ds/multimap_text_insert_timing_small.cc
The test checks the insert-time scalability of different "multimap" designs.
22.4.2.3.3.2

Results

The graphic below show the results for "multimaps" which use a tree-based container for primary keys.

The GNU C++ Library Manual

245 / 399

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_mmap
std::
multimap
rb_tree_mmap_lu_mtf_set
tree

Tag
Node_Upd
ate
Mapped

Details

Parameter

Details

Update_Po
licy

lu_move_t
o_front_p
olicy

Comb_Hash
_Fn

direct_ma
sk_range_
hashing

rb_tree_
tag
null_node
_update
list_upd
ate

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
rb_tree_
Tag
tree
tag
Node_Upd
null_node
ate
_update
Mapped

cc_hash_t
able

Parameter

Details

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type

246 / 399

Details

Parameter

Resize_Po
licy

Details

hash_stan
dard_resi
ze_policy

Parameter
Size_Pol
icy

Trigger_P
olicy

Details
hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

The graphic below show the results for "multimaps" which use a hash-based container for primary keys.

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_mmap
std::tr1:
:
unordered
_multimap

Details

Parameter

Details

Parameter

Details

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type
rb_tree_mmap_lu_mtf_set
cc_hash_
table

Comb_Hash
_Fn

Resize_Po
licy

247 / 399

Details

Parameter

Parameter

Details

direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

Mapped

Details

list_upd
ate

Update_Po
licy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2
lu_move_t
o_front_p
olicy

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
direct_ma
Comb_Hash
sk_range_
cc_hash_
_Fn
hashing
table
Resize_Po
licy

hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

Mapped

cc_hash_t
able

Comb_Hash
_Fn

Resize_Po
licy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2
direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

22.4.2.3.3.3

Observations

See Observations::Mapping-Semantics Considerations.

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

The GNU C++ Library Manual

22.4.2.3.4
22.4.2.3.4.1

248 / 399

Text insert with Small Secondary-to-Primary Key Ratios
Description

This test inserts a number of pairs into a container. The first item of each pair is a string from an arbitrary text [wickland96thirty],
and the second is a uniform integer. The container is a "multimap" - it considers the first member of each pair as a primary key,
and the second member of each pair as a secondary key. There are 400 distinct primary keys, and the ratio of secondary keys to
primary keys ranges from 1 to 5.
The test measures the average insert-time as a function of the number of values inserted. For this library’s containers, it inserts a
primary key into the primary associative container, then a secondary key into the secondary associative container. For the native
multimaps, it obtains a range using std::equal_range, and inserts a value only if it was not contained already.
It uses the test file: performance/ext/pb_ds/multimap_text_insert_timing_large.cc
The test checks the insert-time scalability of different "multimap" designs.
22.4.2.3.4.2

Results

The graphic below show the results for "multimaps" which use a tree-based container for primary keys.

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type
n_mmap
std::
multimap
rb_tree_mmap_lu_mtf_set
tree

Tag
Node_Upd
ate
Mapped

249 / 399

Details

Parameter

Details

Update_Po
licy

lu_move_t
o_front_p
olicy

Comb_Hash
_Fn

direct_ma
sk_range_
hashing

Parameter

Details

rb_tree_
tag
null_node
_update
list_upd
ate

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
rb_tree_
Tag
tree
tag
Node_Upd
null_node
ate
_update
Mapped

cc_hash_t
able

Resize_Po
licy

hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

The graphic below show the results for "multimaps" which use a hash-based container for primary keys.

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

The GNU C++ Library Manual

250 / 399

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_mmap
std::tr1:
:
unordered
_multimap
rb_tree_mmap_lu_mtf_set
cc_hash_
table

Comb_Hash
_Fn

Resize_Po
licy

Details

Parameter

Details

direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

Parameter

Details

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type
Mapped

251 / 399

Details

Parameter

Details

list_upd
ate

Update_Po
licy

lu_move_t
o_front_p
olicy

Parameter

Details

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
direct_ma
Comb_Hash
sk_range_
cc_hash_
_Fn
hashing
table
Resize_Po
licy

hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

Mapped

cc_hash_t
able

Comb_Hash
_Fn

Resize_Po
licy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2
direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

22.4.2.3.4.3

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

Observations

See Observations::Mapping-Semantics Considerations.
22.4.2.3.5
22.4.2.3.5.1

Text insert with Small Secondary-to-Primary Key Ratios Memory Use
Description

This test inserts a number of pairs into a container. The first item of each pair is a string from an arbitrary text [wickland96thirty],
and the second is a uniform integer. The container is a "multimap" - it considers the first member of each pair as a primary key,
and the second member of each pair as a secondary key. There are 100 distinct primary keys, and the ratio of secondary keys to
primary keys ranges to about 20.
The test measures the memory use as a function of the number of values inserted.
It uses the test file: performance/ext/pb_ds/multimap_text_insert_mem_usage_small.cc
The test checks the memory scalability of different "multimap" designs.
22.4.2.3.5.2

Results

The graphic below show the results for "multimaps" which use a tree-based container for primary keys.

The GNU C++ Library Manual

252 / 399

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_mmap
std::
multimap
rb_tree_mmap_lu_mtf_set
tree

Tag
Node_Upd
ate
Mapped

Details

Parameter

Details

Update_Po
licy

lu_move_t
o_front_p
olicy

Comb_Hash
_Fn

direct_ma
sk_range_
hashing

rb_tree_
tag
null_node
_update
list_upd
ate

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
rb_tree_
Tag
tree
tag
Node_Upd
null_node
ate
_update
Mapped

cc_hash_t
able

Parameter

Details

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type

253 / 399

Details

Parameter

Resize_Po
licy

Details

hash_stan
dard_resi
ze_policy

Parameter
Size_Pol
icy

Trigger_P
olicy

Details
hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

The graphic below show the results for "multimaps" which use a hash-based container for primary keys.

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_mmap
std::tr1:
:
unordered
_multimap

Details

Parameter

Details

Parameter

Details

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type
rb_tree_mmap_lu_mtf_set
cc_hash_
table

Comb_Hash
_Fn

Resize_Po
licy

254 / 399

Details

Parameter

Parameter

Details

direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

Mapped

Details

list_upd
ate

Update_Po
licy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2
lu_move_t
o_front_p
olicy

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
direct_ma
Comb_Hash
sk_range_
cc_hash_
_Fn
hashing
table
Resize_Po
licy

hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

Mapped

cc_hash_t
able

Comb_Hash
_Fn

Resize_Po
licy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2
direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

22.4.2.3.5.3

Observations

See Observations::Mapping-Semantics Considerations.

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

The GNU C++ Library Manual

22.4.2.3.6
22.4.2.3.6.1

255 / 399

Text insert with Small Secondary-to-Primary Key Ratios Memory Use
Description

This test inserts a number of pairs into a container. The first item of each pair is a string from an arbitrary text [wickland96thirty],
and the second is a uniform integer. The container is a "multimap" - it considers the first member of each pair as a primary key,
and the second member of each pair as a secondary key. There are 100 distinct primary keys, and the ratio of secondary keys to
primary keys ranges to about 20.
The test measures the memory use as a function of the number of values inserted.
It uses the test file: performance/ext/pb_ds/multimap_text_insert_mem_usage_large.cc
The test checks the memory scalability of different "multimap" designs.
22.4.2.3.6.2

Results

The graphic below show the results for "multimaps" which use a tree-based container for primary keys.

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_mmap
std::
multimap

Details

Parameter

Details

Parameter

Details

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type
rb_tree_mmap_lu_mtf_set
tree

Tag
Node_Upd
ate
Mapped

256 / 399

Details

Parameter

Details

Update_Po
licy

lu_move_t
o_front_p
olicy

Comb_Hash
_Fn

direct_ma
sk_range_
hashing

Parameter

Details

rb_tree_
tag
null_node
_update
list_upd
ate

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
rb_tree_
Tag
tree
tag
Node_Upd
null_node
ate
_update
Mapped

cc_hash_t
able

Resize_Po
licy

hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

The graphic below show the results for "multimaps" which use a hash-based container for primary keys.

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

The GNU C++ Library Manual

257 / 399

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating
Parameter
Type
n_hash_mmap
std::tr1:
:
unordered
_multimap
rb_tree_mmap_lu_mtf_set
cc_hash_
table

Comb_Hash
_Fn

Resize_Po
licy

Details

Parameter

Details

direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

Parameter

Details

The GNU C++ Library Manual

Name/Instantiating
Parameter
Type
Mapped

258 / 399

Details

Parameter

Details

list_upd
ate

Update_Po
licy

lu_move_t
o_front_p
olicy

Parameter

Details

rb_tree_mmap_cc_hash_mask_exp_1div2_nsth_set
direct_ma
Comb_Hash
sk_range_
cc_hash_
_Fn
hashing
table
Resize_Po
licy

hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

Mapped

cc_hash_t
able

Comb_Hash
_Fn

Resize_Po
licy

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2
direct_ma
sk_range_
hashing
hash_stan
dard_resi
ze_policy

Size_Pol
icy

Trigger_P
olicy

22.4.2.3.6.3

hash_expo
nential_s
ize_pol
icy
hash_load
_check_re
size_trig
ger with
α min = 1/8 and
α max = 1/2

Observations

See Observations::Mapping-Semantics Considerations.
22.4.2.4

Priority Queue

22.4.2.4.1
22.4.2.4.1.1

Text push
Description

This test inserts a number of values with keys from an arbitrary text ([ wickland96thirty ]) into a container using push. It
measures the average time for push as a function of the number of values pushed.
It uses the test file: performance/ext/pb_ds/priority_queue_text_push_timing.cc
The test checks the effect of different underlying data structures.
22.4.2.4.1.2

Results

The two graphics below show the results for the native priority_queues and this library’s priority_queues.
The graphic immediately below shows the results for the native priority_queue type instantiated with different underlying container types versus several different versions of library’s priority_queues.

The GNU C++ Library Manual

259 / 399

Average time (sec.)

5.80e-05
4.64e-05
3.48e-05
2.32e-05
1.16e-05
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

binary_heap
rc_binomial_heap
n_pq_deque
binomial_heap
n_pq_vector
thin_heap
pairing_heap

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_pq_vector
std::priority_queue
n_pq_deque
std::priority_queue
binary_heap
priority_queue
binomial_heap
priority_queue
rc_binomial_heap
priority_queue
thin_heap
priority_queue
pairing_heap
priority_queue

Parameter

Details

Sequence

std::vector

Sequence

std::deque

Tag

binary_heap_tag

Tag

binomial_heap_tag

Tag

rc_binomial_heap_tag

Tag

thin_heap_tag

Tag

pairing_heap_tag

The graphic below shows the results for the binary-heap based native priority queues and this library’s pairing-heap priority_queue data structures.

Average time (sec.)

The GNU C++ Library Manual

260 / 399

7.75e-08
5.81e-08
3.87e-08
1.94e-08
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_pq_deque
n_pq_vector
thin_heap
pairing_heap

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_pq_vector
std::priority_queue
n_pq_deque
std::priority_queue
thin_heap
priority_queue
pairing_heap
priority_queue

22.4.2.4.1.3

Parameter

Details

Sequence

std::vector

Sequence

std::deque

Tag

thin_heap_tag

Tag

pairing_heap_tag

Observations

Pairing heaps (priority_queue with Tag = pairing_heap_tag) are the most suited for sequences of push and pop
operations of non-primitive types (e.g. std::strings). (See Priority Queue Text push and pop Timing Test.) They are less
constrained than binomial heaps, e.g., and since they are node-based, they outperform binary heaps. (See Priority Queue Random
Integer push Timing Test for the case of primitive types.)
The standard’s priority queues do not seem to perform well in this case: the std::vector implementation needs to perform a
logarithmic sequence of string operations for each operation, and the deque implementation is possibly hampered by its need to
manipulate a relatively-complex type (deques support a O(1) push_front, even though it is not used by std::priority_
queue.)
22.4.2.4.2
22.4.2.4.2.1

Text push and pop
Description

This test inserts a number of values with keys from an arbitrary text ([ wickland96thirty ]) into a container using push , then
removes them using pop . It measures the average time for push as a function of the number of values.
It uses the test file: performance/ext/pb_ds/priority_queue_text_push_pop_timing.cc

The GNU C++ Library Manual

261 / 399

The test checks the effect of different underlying data structures.
22.4.2.4.2.2

Results

The two graphics below show the results for the native priority_queues and this library’s priority_queues.
The graphic immediately below shows the results for the native priority_queue type instantiated with different underlying container types versus several different versions of library’s priority_queues.

Average time (sec.)

5.88e-05
4.71e-05
3.53e-05
2.35e-05
1.18e-05
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

binary_heap
rc_binomial_heap
thin_heap
binomial_heap
n_pq_deque
pairing_heap
n_pq_vector

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_pq_vector
std::priority_queue
n_pq_deque
std::priority_queue
binary_heap
priority_queue
binomial_heap
priority_queue
rc_binomial_heap
priority_queue
thin_heap
priority_queue
pairing_heap
priority_queue

Parameter

Details

Sequence

std::vector

Sequence

std::deque

Tag

binary_heap_tag

Tag

binomial_heap_tag

Tag

rc_binomial_heap_tag

Tag

thin_heap_tag

Tag

pairing_heap_tag

The GNU C++ Library Manual

262 / 399

The graphic below shows the results for the native priority queues and this library’s pairing-heap priority_queue data structures.

Average time (sec.)

4.46e-07
3.57e-07
2.68e-07
1.78e-07
8.92e-08
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_pq_deque
pairing_heap
n_pq_vector

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_pq_vector
std::priority_queue adapting
std::vector
n_pq_deque
std::priority_queue
pairing_heap
priority_queue

22.4.2.4.2.3

Parameter

Details

Sequence

std::vector

Sequence

std::deque

Tag

pairing_heap_tag

Observations

These results are very similar to Priority Queue Text push Timing Test. As stated there, pairing heaps (priority_queue with
Tag = pairing_heap_tag) are most suited for push and pop sequences of non-primitive types such as strings. Observing
these two tests, one can note that a pairing heap outperforms the others in terms of push operations, but equals binary heaps
(priority_queue with Tag = binary_heap_tag) if the number of push and pop operations is equal. As the number
of pop operations is at most equal to the number of push operations, pairing heaps are better in this case. See Priority Queue
Random Integer push and pop Timing Test for a case which is different.
22.4.2.4.3
22.4.2.4.3.1

Integer push
Description

This test inserts a number of values with integer keys into a container using push. It measures the average time for push as a
function of the number of values.
It uses the test file: performance/ext/pb_ds/priority_queue_random_int_push_timing.cc
The test checks the effect of different underlying data structures.

The GNU C++ Library Manual

22.4.2.4.3.2

263 / 399

Results

The two graphics below show the results for the native priority_queues and this library’s priority_queues.
The graphic immediately below shows the results for the native priority_queue type instantiated with different underlying container types versus several different versions of library’s priority_queues.

Average time (sec.)

6.90e-06
5.52e-06
4.14e-06
2.76e-06
1.38e-06
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

binary_heap
rc_binomial_heap
binomial_heap
thin_heap
pairing_heap
n_pq_deque
n_pq_vector

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_pq_vector
std::priority_queue
n_pq_deque
std::priority_queue
binary_heap
priority_queue
binomial_heap
priority_queue
rc_binomial_heap
priority_queue
thin_heap
priority_queue
pairing_heap
priority_queue

Parameter

Details

Sequence

std::vector

Sequence

std::deque

Tag

binary_heap_tag

Tag

binomial_heap_tag

Tag

rc_binomial_heap_tag

Tag

thin_heap_tag

Tag

pairing_heap_tag

The graphic below shows the results for the binary-heap based native priority queues and this library’s priority_queue data
structures.

The GNU C++ Library Manual

264 / 399

Average time (sec.)

6.90e-06
5.52e-06
4.14e-06
2.76e-06
1.38e-06
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

binary_heap
n_pq_deque
n_pq_vector

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_pq_vector
std::priority_queue adapting
std::vector
n_pq_deque
std::priority_queue
binary_heap
priority_queue

22.4.2.4.3.3

Parameter

Details

Sequence

std::vector

Sequence

std::deque

Tag

binary_heap_tag

Observations

Binary heaps are the most suited for sequences of push and pop operations of primitive types (e.g. ints). They are less
constrained than any other type, and since it is very efficient to store such types in arrays, they outperform even pairing heaps.
(See Priority Queue Text push Timing Test for the case of non-primitive types.)
22.4.2.4.4
22.4.2.4.4.1

Integer push
Description

This test inserts a number of values with integer keys into a container using push , then removes them using pop . It measures
the average time for push and pop as a function of the number of values.
It uses the test file: performance/ext/pb_ds/priority_queue_random_int_push_pop_timing.cc
The test checks the effect of different underlying data structures.
22.4.2.4.4.2

Results

The graphic immediately below shows the results for the native priority_queue type instantiated with different underlying container types versus several different versions of library’s priority_queues.

The GNU C++ Library Manual

265 / 399

Average time (sec.)

6.70e-06
5.36e-06
4.02e-06
2.68e-06
1.34e-06
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

binary_heap
thin_heap
rc_binomial_heap
binomial_heap
pairing_heap
n_pq_deque
n_pq_vector

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_pq_vector
std::priority_queue
n_pq_deque
std::priority_queue
binary_heap
priority_queue
binomial_heap
priority_queue
rc_binomial_heap
priority_queue
thin_heap
priority_queue
pairing_heap
priority_queue

22.4.2.4.4.3

Parameter

Details

Sequence

std::vector

Sequence

std::deque

Tag

binary_heap_tag

Tag

binomial_heap_tag

Tag

rc_binomial_heap_tag

Tag

thin_heap_tag

Tag

pairing_heap_tag

Observations

Binary heaps are the most suited for sequences of push and pop operations of primitive types (e.g. ints). This is explained in
Priority Queue Random Int push Timing Test. (See Priority Queue Text push Timing Test for the case of primitive types.)
At first glance it seems that the standard’s vector-based priority queue is approximately on par with this library’s corresponding
priority queue. There are two differences however:
1. The standard’s priority queue does not downsize the underlying vector (or deque) as the priority queue becomes smaller
(see Priority Queue Text pop Memory Use Test). It is therefore gaining some speed at the expense of space.

The GNU C++ Library Manual

266 / 399

2. From Priority Queue Random Integer push and pop Timing Test, it seems that the standard’s priority queue is slower in
terms of push operations. Since the number of pop operations is at most that of push operations, the test here is the
"best" for the standard’s priority queue.
22.4.2.4.5
22.4.2.4.5.1

Text pop Memory Use
Description

This test inserts a number of values with keys from an arbitrary text ([ wickland96thirty ]) into a container, then pops them until
only one is left in the container. It measures the memory use as a function of the number of values pushed to the container.
It uses the test file: performance/ext/pb_ds/priority_queue_text_pop_mem_usage.cc
The test checks the effect of different underlying data structures.
22.4.2.4.5.2

Results

The graphic immediately below shows the results for the native priority_queue type instantiated with different underlying container types versus several different versions of library’s priority_queues.

Memory (bytes)

2.29e+04
1.97e+04
1.64e+04
1.31e+04
9.83e+03
6.55e+03
3.28e+03
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_pq_vector
n_pq_deque
binary_heap
thin_heap
binomial_heap
rc_binomial_heap
pairing_heap

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_pq_vector
std::priority_queue
n_pq_deque
std::priority_queue
binary_heap
priority_queue

Parameter

Details

Sequence

std::vector

Sequence

std::deque

Tag

binary_heap_tag

The GNU C++ Library Manual

Name/Instantiating Type
binomial_heap
priority_queue
rc_binomial_heap
priority_queue
thin_heap
priority_queue
pairing_heap
priority_queue

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Parameter

Details

Tag

binomial_heap_tag

Tag

rc_binomial_heap_tag

Tag

thin_heap_tag

Tag

pairing_heap_tag

Observations

The priority queue implementations (excluding the standard’s) use memory proportionally to the number of values they hold:
node-based implementations (e.g., a pairing heap) do so naturally; this library’s binary heap de-allocates memory when a certain
lower threshold is exceeded.
Note from Priority Queue Text push and pop Timing Test and Priority Queue Random Integer push and pop Timing Test that
this does not impede performance compared to the standard’s priority queues.
See Hash-Based Erase Memory Use Test for a similar phenomenon regarding priority queues.
22.4.2.4.6
22.4.2.4.6.1

Text join
Description

This test inserts a number of values with keys from an arbitrary text ([ wickland96thirty ]) into two containers, then merges the
containers. It uses join for this library’s priority queues; for the standard’s priority queues, it successively pops values from
one container and pushes them into the other. The test measures the average time as a function of the number of values.
It uses the test file: performance/ext/pb_ds/priority_queue_text_join_timing.cc
The test checks the effect of different underlying data structures.
22.4.2.4.6.2

Results

The graphic immediately below shows the results for the native priority_queue type instantiated with different underlying container types versus several different versions of library’s priority_queues.

Average time (sec.)

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2.67e-06
2.00e-06
1.33e-06
6.67e-07
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_pq_deque
n_pq_vector
binary_heap
thin_heap
binomial_heap
pairing_heap
rc_binomial_heap

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_pq_vector
std::priority_queue
n_pq_deque
std::priority_queue
binary_heap
priority_queue
binomial_heap
priority_queue
rc_binomial_heap
priority_queue
thin_heap
priority_queue
pairing_heap
priority_queue

22.4.2.4.6.3

Parameter

Details

Sequence

std::vector

Sequence

std::deque

Tag

binary_heap_tag

Tag

binomial_heap_tag

Tag

rc_binomial_heap_tag

Tag

thin_heap_tag

Tag

pairing_heap_tag

Observations

In this test the node-based heaps perform join in either logarithmic or constant time. The binary heap requires linear time,
since the well-known heapify algorithm [clrs2001] is linear.
It would be possible to apply the heapify algorithm to the standard containers, if they would support iteration (which they don’t).
Barring iterators, it is still somehow possible to perform linear-time merge on a std::vector-based standard priority queue,
using top() and size() (since they are enough to expose the underlying array), but this is impossible for a std::dequebased standard priority queue. Without heapify, the cost is super-linear.

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Text modify Up
Description

This test inserts a number of values with keys from an arbitrary text ([ wickland96thirty ]) into into a container then modifies
each one "up" (i.e., it makes it larger). It uses modify for this library’s priority queues; for the standard’s priority queues, it pops
values from a container until it reaches the value that should be modified, then pushes values back in. It measures the average
time for modify as a function of the number of values.
It uses the test file: performance/ext/pb_ds/priority_queue_text_modify_up_timing.cc
The test checks the effect of different underlying data structures for graph algorithms settings. Note that making an arbitrary
value larger (in the sense of the priority queue’s comparison functor) corresponds to decrease-key in standard graph algorithms
[clrs2001].
22.4.2.4.7.2

Results

The two graphics below show the results for the native priority_queues and this library’s priority_queues.
The graphic immediately below shows the results for the native priority_queue type instantiated with different underlying container types versus several different versions of library’s priority_queues.

Average time (sec.)

4.40e-04
3.52e-04
2.64e-04
1.76e-04
8.80e-05
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_pq_deque
n_pq_vector
binary_heap
rc_binomial_heap
pairing_heap
binomial_heap
thin_heap

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
n_pq_vector
std::priority_queue
n_pq_deque
std::priority_queue

Parameter

Details

Sequence

std::vector

Sequence

std::deque

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Name/Instantiating Type
binary_heap
priority_queue
binomial_heap
priority_queue
rc_binomial_heap
priority_queue
thin_heap
priority_queue
pairing_heap
priority_queue

Parameter

Details

Tag

binary_heap_tag

Tag

binomial_heap_tag

Tag

rc_binomial_heap_tag

Tag

thin_heap_tag

Tag

pairing_heap_tag

The graphic below shows the results for the native priority queues and this library’s pairing and thin heap priority_queue data
structures.

Average time (sec.)

1.36e-07
1.09e-07
8.18e-08
5.45e-08
2.73e-08
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

pairing_heap
thin_heap

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
thin_heap
priority_queue
pairing_heap
priority_queue

22.4.2.4.7.3

Parameter

Details

Tag

thin_heap_tag

Tag

pairing_heap_tag

Observations

As noted above, increasing an arbitrary value (in the sense of the priority queue’s comparison functor) is very common in graphrelated algorithms. In this case, a thin heap (priority_queue with Tag = thin_heap_tag) outperforms a pairing heap
(priority_queue with Tag = pairing_heap_tag). Conversely, Priority Queue Text push Timing Test, Priority Queue
Text push and pop Timing Test, Priority Queue Random Integer push Timing Test, and Priority Queue Random Integer push
and pop Timing Test show that the situation is reversed for other operations. It is not clear when to prefer one of these two
different types.

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In this test this library’s binary heaps effectively perform modify in linear time. As explained in Priority Queue Design::Traits,
given a valid point-type iterator, a binary heap can perform modify logarithmically. The problem is that binary heaps invalidate
their find iterators with each modifying operation, and so the only way to obtain a valid point-type iterator is to iterate using a
range-type iterator until finding the appropriate value, then use the range-type iterator for the modify operation.
The explanation for the standard’s priority queues’ performance is similar to that in Priority Queue Text join Timing Test.
22.4.2.4.8
22.4.2.4.8.1

Text modify Down
Description

This test inserts a number of values with keys from an arbitrary text ([ wickland96thirty ]) into into a container then modifies
each one "down" (i.e., it makes it smaller). It uses modify for this library’s priority queues; for the standard’s priority queues,
it pops values from a container until it reaches the value that should be modified, then pushes values back in. It measures the
average time for modify as a function of the number of values.
It uses the test file: performance/ext/pb_ds/priority_queue_text_modify_down_timing.cc
The main purpose of this test is to contrast Priority Queue Text modify Up Timing Test.
22.4.2.4.8.2

Results

The two graphics below show the results for the native priority_queues and this library’s priority_queues.
The graphic immediately below shows the results for the native priority_queue type instantiated with different underlying container types versus several different versions of library’s priority_queues.

Average time (sec.)

4.20e-04
3.36e-04
2.52e-04
1.68e-04
8.40e-05
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

n_pq_deque
n_pq_vector
binary_heap
thin_heap
rc_binomial_heap
binomial_heap
pairing_heap

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.

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Name/Instantiating Type
n_pq_vector
std::priority_queue
n_pq_deque
std::priority_queue
binary_heap
priority_queue
binomial_heap
priority_queue
rc_binomial_heap
priority_queue
thin_heap
priority_queue
pairing_heap
priority_queue

Parameter

Details

Sequence

std::vector

Sequence

std::deque

Tag

binary_heap_tag

Tag

binomial_heap_tag

Tag

rc_binomial_heap_tag

Tag

thin_heap_tag

Tag

pairing_heap_tag

The graphic below shows the results for the native priority queues and this library’s pairing and thin heap priority_queue data
structures.

Average time (sec.)

6.26e-07
5.01e-07
3.76e-07
2.51e-07
1.25e-07
0.00e+00
2200

2000

1800

1600

1400

1200

1000

800

600

400

200

0

Size

thin_heap
pairing_heap

The abbreviated names in the legend of the graphic above are instantiated with the types in the following table.
Name/Instantiating Type
thin_heap
priority_queue
pairing_heap
priority_queue

22.4.2.4.8.3

Parameter

Details

Tag

thin_heap_tag

Tag

pairing_heap_tag

Observations

Most points in these results are similar to Priority Queue Text modify Up Timing Test.
It is interesting to note, however, that as opposed to that test, a thin heap (priority_queue with Tag = thin_heap_tag) is

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outperformed by a pairing heap (priority_queue with Tag = pairing_heap_tag). In this case, both heaps essentially
perform an erase operation followed by a push operation. As the other tests show, a pairing heap is usually far more efficient
than a thin heap, so this is not surprising.
Most algorithms that involve priority queues increase values (in the sense of the priority queue’s comparison functor), and so
Priority Queue Text modify Up Timing Test - is more interesting than this test.
22.4.2.5

Observations

22.4.2.5.1
22.4.2.5.1.1

Associative
Underlying Data-Structure Families

In general, hash-based containers have better timing performance than containers based on different underlying-data structures.
The main reason to choose a tree-based or trie-based container is if a byproduct of the tree-like structure is required: either orderpreservation, or the ability to utilize node invariants. If memory-use is the major factor, an ordered-vector tree gives optimal
results (albeit with high modificiation costs), and a list-based container gives reasonable results.
22.4.2.5.1.2

Hash-Based Containers

Hash-based containers are typically either collision chaining or probing. Collision-chaining containers are more flexible internally, and so offer better timing performance. Probing containers, if used for simple value-types, manage memory more
efficiently (they perform far fewer allocation-related calls). In general, therefore, a collision-chaining table should be used. A
probing container, conversely, might be used efficiently for operations such as eliminating duplicates in a sequence, or counting
the number of occurrences within a sequence. Probing containers might be more useful also in multithreaded applications where
each thread manipulates a hash-based container: in the standard, allocators have class-wise semantics (see [meyers96more] Item 10); a probing container might incur less contention in this case.
22.4.2.5.1.3

Hash Policies

In hash-based containers, the range-hashing scheme seems to affect performance more than other considerations. In most settings,
a mask-based scheme works well (or can be made to work well). If the key-distribution can be estimated a-priori, a simple hash
function can produce nearly uniform hash-value distribution. In many other cases (e.g., text hashing, floating-point hashing),
the hash function is powerful enough to generate hash values with good uniformity properties [knuth98sorting]; a modulo-based
scheme, taking into account all bits of the hash value, appears to overlap the hash function in its effort.
The range-hashing scheme determines many of the other policies. A mask-based scheme works well with an exponential-size
policy; for probing-based containers, it goes well with a linear-probe function.
An orthogonal consideration is the trigger policy. This presents difficult tradeoffs. E.g., different load factors in a load-check
trigger policy yield a space/amortized-cost tradeoff.
22.4.2.5.1.4

Branch-Based Containers

In general, there are several families of tree-based underlying data structures: balanced node-based trees (e.g., red-black or AVL
trees), high-probability balanced node-based trees (e.g., random treaps or skip-lists), competitive node-based trees (e.g., splay
trees), vector-based "trees", and tries. (Additionally, there are disk-residing or network-residing trees, such as B-Trees and their
numerous variants. An interface for this would have to deal with the execution model and ACID guarantees; this is out of the
scope of this library.) Following are some observations on their application to different settings.
Of the balanced node-based trees, this library includes a red-black tree, as does standard (in practice). This type of tree is the
"workhorse" of tree-based containers: it offers both reasonable modification and reasonable lookup time. Unfortunately, this data
structure stores a huge amount of metadata. Each node must contain, besides a value, three pointers and a boolean. This type
might be avoided if space is at a premium [austern00noset].
High-probability balanced node-based trees suffer the drawbacks of deterministic balanced trees. Although they are fascinating
data structures, preliminary tests with them showed their performance was worse than red-black trees. The library does not
contain any such trees, therefore.

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Competitive node-based trees have two drawbacks. They are usually somewhat unbalanced, and they perform a large number of
comparisons. Balanced trees perform one comparison per each node they encounter on a search path; a splay tree performs two
comparisons. If the keys are complex objects, e.g., std::string, this can increase the running time. Conversely, such trees
do well when there is much locality of reference. It is difficult to determine in which case to prefer such trees over balanced trees.
This library includes a splay tree.
Ordered-vector trees use very little space [austern00noset]. They do not have any other advantages (at least in this implementation).
Large-fan-out PATRICIA tries have excellent lookup performance, but they do so through maintaining, for each node, a miniature
"hash-table". Their space efficiency is low, and their modification performance is bad. These tries might be used for semi-static
settings, where order preservation is important. Alternatively, red-black trees cross-referenced with hash tables can be used.
[okasaki98mereable] discusses small-fan-out PATRICIA tries for integers, but the cited results seem to indicate that the amortized
cost of maintaining such trees is higher than that of balanced trees. Moderate-fan-out trees might be useful for sequences where
each element has a limited number of choices, e.g., DNA strings.
22.4.2.5.1.5

Mapping-Semantics

Different mapping semantics were discussed in the introduction and design sections.Here the focus will be on the case where a
keys can be composed into primary keys and secondary keys. (In the case where some keys are completely identical, it is trivial
that one should use an associative container mapping values to size types.) In this case there are (at least) five possibilities:
1. Use an associative container that allows equivalent-key values (such as std::multimap)
2. Use a unique-key value associative container that maps each primary key to some complex associative container of secondary keys, say a tree-based or hash-based container.
3. Use a unique-key value associative container that maps each primary key to some simple associative container of secondary
keys, say a list-based container.
4. Use a unique-key value associative container that maps each primary key to some non-associative container (e.g., std::
vector)
5. Use a unique-key value associative container that takes into account both primary and secondary keys.
Stated simply: there is a simple answer for this. (Excluding option 1, which should be avoided in all cases).
If the expected ratio of secondary keys to primary keys is small, then 3 and 4 seem reasonable. Both types of secondary containers
are relatively lightweight (in terms of memory use and construction time), and so creating an entire container object for each
primary key is not too expensive. Option 4 might be preferable to option 3 if changing the secondary key of some primary key
is frequent - one cannot modify an associative container’s key, and the only possibility, therefore, is erasing the secondary key
and inserting another one instead; a non-associative container, conversely, can support in-place modification. The actual cost
of erasing a secondary key and inserting another one depends also on the allocator used for secondary associative-containers
(The tests above used the standard allocator, but in practice one might choose to use, e.g., [boost_pool]). Option 2 is definitely
an overkill in this case. Option 1 loses out either immediately (when there is one secondary key per primary key) or almost
immediately after that. Option 5 has the same drawbacks as option 2, but it has the additional drawback that finding all values
whose primary key is equivalent to some key, might be linear in the total number of values stored (for example, if using a
hash-based container).
If the expected ratio of secondary keys to primary keys is large, then the answer is more complicated. It depends on the distribution of secondary keys to primary keys, the distribution of accesses according to primary keys, and the types of operations most
frequent.
To be more precise, assume there are m primary keys, primary key i is mapped to ni secondary keys, and each primary key is
mapped, on average, to n secondary keys (i.e., E(ni ) = n).
Suppose one wants to find a specific pair of primary and secondary keys. Using 1 with a tree based container (std::multi
map), the expected cost is E(Θ(log(m) + ni )) = Θ(log(m) + n); using 1 with a hash-based container (std::tr1::unordere
d_multimap), the expected cost is Θ(n). Using 2 with a primary hash-based container and secondary hash-based containers,
the expected cost is O(1); using 2 with a primary tree-based container and secondary tree-based containers, the expected cost is
(using the Jensen inequality [motwani95random]) E(O(log(m) + log(ni )) = O(log(m)) + E(O(log(ni )) = O(log(m)) + O(log(n)),

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assuming that primary keys are accessed equiprobably. 3 and 4 are similar to 1, but with lower constants. Using 5 with a
hash-based container, the expected cost is O(1); using 5 with a tree based container, the cost is E(Θ(log(mn))) = Θ(log(m) +
log(n)).
Suppose one needs the values whose primary key matches some given key. Using 1 with a hash-based container, the expected
cost is Θ(n), but the values will not be ordered by secondary keys (which may or may not be required); using 1 with a tree-based
container, the expected cost is Θ(log(m) + n), but with high constants; again the values will not be ordered by secondary keys.
2, 3, and 4 are similar to 1, but typically with lower constants (and, additionally, if one uses a tree-based container for secondary
keys, they will be ordered). Using 5 with a hash-based container, the cost is Θ(mn).
Suppose one wants to assign to a primary key all secondary keys assigned to a different primary key. Using 1 with a hash-based
container, the expected cost is Θ(n), but with very high constants; using 1 with a tree-based container, the cost is Θ(nlog(mn)).
Using 2, 3, and 4, the expected cost is Θ(n), but typically with far lower costs than 1. 5 is similar to 1.
22.4.2.5.2
22.4.2.5.2.1

Priority_Queue
Complexity

The following table shows the complexities of the different underlying data structures in terms of orders of growth. It is interesting
to note that this table implies something about the constants of the operations as well (see Amortized push and pop operations).

std::priori
ty_queue
priority_qu
eue 
priority_qu
eue 
priority_qu
eue 
priority_qu
eue 
priority_qu
eue

push
Θ(n) worst
Θ(log(n))
amortized

pop

modify

erase

join

Θ(log(n)) Worst

Θ(n log(n))
Worst [std note 1]

Θ(n log(n))

Θ(n log(n))

[std note 2]

[std note 1]

O(1)

Θ(n) worst
Θ(log(n))
amortized

Θ(n) worst
Θ(log(n))
amortized

Θ(n) worst
Θ(log(n))
amortized

O(1)

Θ(n) worst
Θ(log(n))
amortized

Θ(n) worst
Θ(log(n))
amortized

Θ(n)

Θ(n)

Θ(n)

Θ(log(n)) worst
O(1) amortized

Θ(log(n))

Θ(log(n))

Θ(log(n))

Θ(log(n))

O(1)

Θ(log(n))

Θ(log(n))

Θ(log(n))

Θ(log(n))

O(1)

Θ(n) worst
Θ(log(n))
amortized

Θ(log(n)) worst
O(1) amortized,
or Θ(log(n))
amortized

Θ(n) worst
Θ(log(n))
amortized

Θ(n)

[thin_heap_note]

[std note 1] This is not a property of the algorithm, but rather due to the fact that the standard’s priority queue implementation
does not support iterators (and consequently the ability to access a specific value inside it). If the priority queue is adapting an
std::vector, then it is still possible to reduce this to Θ(n) by adapting over the standard’s adapter and using the fact that top
returns a reference to the first value; if, however, it is adapting an std::deque, then this is impossible.
[std note 2] As with [std note 1], this is not a property of the algorithm, but rather the standard’s implementation. Again, if the
priority queue is adapting an std::vector then it is possible to reduce this to Θ(n), but with a very high constant (one must
call std::make_heap which is an expensive linear operation); if the priority queue is adapting an std::deque, then this is
impossible.
[thin_heap_note] A thin heap has Θ(log(n)) worst case modify time always, but the amortized time depends on the nature of

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the operation: I) if the operation increases the key (in the sense of the priority queue’s comparison functor), then the amortized
time is O(1), but if II) it decreases it, then the amortized time is the same as the worst case time. Note that for most algorithms,
I) is important and II) is not.
22.4.2.5.2.2

Amortized push and pop operations

In many cases, a priority queue is needed primarily for sequences of push and pop operations. All of the underlying data
structures have the same amortized logarithmic complexity, but they differ in terms of constants.
The table above shows that the different data structures are "constrained" in some respects. In general, if a data structure has lower
worst-case complexity than another, then it will perform slower in the amortized sense. Thus, for example a redundant-counter
binomial heap (priority_queue with Tag = rc_binomial_heap_tag) has lower worst-case push performance than a
binomial heap (priority_queue with Tag = binomial_heap_tag), and so its amortized push performance is slower
in terms of constants.
As the table shows, the "least constrained" underlying data structures are binary heaps and pairing heaps. Consequently, it is not
surprising that they perform best in terms of amortized constants.
1. Pairing heaps seem to perform best for non-primitive types (e.g., std::strings), as shown by Priority Queue Text
push Timing Test and Priority Queue Text push and pop Timing Test
2. binary heaps seem to perform best for primitive types (e.g., ints), as shown by Priority Queue Random Integer push
Timing Test and Priority Queue Random Integer push and pop Timing Test.
22.4.2.5.2.3

Graph Algorithms

In some graph algorithms, a decrease-key operation is required [clrs2001]; this operation is identical to modify if a value is
increased (in the sense of the priority queue’s comparison functor). The table above and Priority Queue Text modify Up Timing
Test show that a thin heap (priority_queue with Tag = thin_heap_tag) outperforms a pairing heap (priority_qu
eue with Tag = Tag = pairing_heap_tag), but the rest of the tests show otherwise.
This makes it difficult to decide which implementation to use in this case. Dijkstra’s shortest-path algorithm, for example,
requires Θ(n) push and pop operations (in the number of vertices), but O(n2 ) modify operations, which can be in practice
Θ(n) as well. It is difficult to find an a-priori characterization of graphs in which the actual number of modify operations will
dwarf the number of push and pop operations.

22.5

Acknowledgments

Written by Ami Tavory and Vladimir Dreizin (IBM Haifa Research Laboratories), and Benjamin Kosnik (Red Hat).
This library was partially written at IBM’s Haifa Research Labs. It is based heavily on policy-based design and uses many useful
techniques from Modern C++ Design: Generic Programming and Design Patterns Applied by Andrei Alexandrescu.
Two ideas are borrowed from the SGI-STL implementation:
1. The prime-based resize policies use a list of primes taken from the SGI-STL implementation.
2. The red-black trees contain both a root node and a header node (containing metadata), connected in a way that forward and
reverse iteration can be performed efficiently.
Some test utilities borrow ideas from boost::timer.
We would like to thank Scott Meyers for useful comments (without attributing to him any flaws in the design or implementation
of the library).
We would like to thank Matt Austern for the suggestion to include tries.

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[74] N. M. Jossutis , The C++ Standard Library - A Tutorial and Reference , 2001 , Addison-Wesley Publishing
Company .
[75] Haim Kaplan and Robert E. Tarjan , New Heap Data Structures , 1999 .
[76] Angelika Langer and Klaus Kleft , Are Set Iterators Mutable or Immutable? , October 2000 , C/C++ Users
Jornal .
[77] D. E. Knuth , The Art of Computer Programming - Sorting and Searching , 1998 , Addison-Wesley Publishing
Company .
[78] B. Liskov , Data abstraction and hierarchy , May 1998 , SIGPLAN Notices 23 .
[79] W. Litwin , Linear hashing: A new tool for file and table addressing , June 1980 , Proceedings of International
Conference on Very Large Data Bases .
[80] Maverick Woo , Deamortization - Part 2: Binomial Heaps , 2005 .

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[81] Scott Meyers , More Effective C++: 35 New Ways to Improve Your Programs and Designs , 1996 , AddisonWesley Publishing Company .
[82] Scott Meyers , How Non-Member Functions Improve Encapsulation , 2000 , C/C++ Users Journal .
[83] Scott Meyers , Effective STL: 50 Specific Ways to Improve Your Use of the Standard Template Library , 2001 ,
Addison-Wesley Publishing Company .
[84] Scott Meyers , Class Template, Member Template - or Both? , 2003 , C/C++ Users Journal .
[85] R. Motwani and P. Raghavan , Randomized Algorithms , 2003 , Cambridge University Press .
[86] COM: Component Model Object Technologies , Microsoft .
[87] David R. Musser , Rationale for Adding Hash Tables to the C++ Standard Template Library , 1995 .
[88] David R. Musser and A. Saini , STL Tutorial and Reference Guide , 1996 , Addison-Wesley Publishing Company .
[89] Mark Nelson , Priority Queues and the STL , January 1996 , Dr. Dobbs Journal .
[90] C. Okasaki and A. Gill , Fast mergeable integer maps , September 1998 , In Workshop on ML .
[91] Matt Austern , Standard Template Library Programmer’s Guide , SGI .
[92] select
[93] D. D. Sleator and R. E. Tarjan , Amortized Efficiency of List Update Problems , 1984 , ACM Symposium on
Theory of Computing .
[94] D. D. Sleator and R. E. Tarjan , Self-Adjusting Binary Search Trees , 1985 , ACM Symposium on Theory of
Computing .
[95] A. A. Stepanov and M. Lee , The Standard Template Library , 1984 .
[96] Bjarne Stroustrup , The C++ Programming Langugage , 1997 , Addison-Wesley Publishing Company .
[97] D. Vandevoorde and N. M. Josuttis , C++ Templates: The Complete Guide , 2002 , Addison-Wesley Publishing
Company .
[98] C. A. Wickland , Thirty Years Among the Dead , 1996 , National Psychological Institute .

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Chapter 23

HP/SGI Extensions
23.1

Backwards Compatibility

A few extensions and nods to backwards-compatibility have been made with containers. Those dealing with older SGI-style
allocators are dealt with elsewhere. The remaining ones all deal with bits:
The old pre-standard bit_vector class is present for backwards compatibility. It is simply a typedef for the vector
specialization.
The bitset class has a number of extensions, described in the rest of this item. First, we’ll mention that this implementation of
bitset is specialized for cases where N number of bits will fit into a single word of storage. If your choice of N is within
that range (<=32 on i686-pc-linux-gnu, for example), then all of the operations will be faster.
There are versions of single-bit test, set, reset, and flip member functions which do no range-checking. If we call them member
functions of an instantiation of bitset, then their names and signatures are:
bitset&
bitset&
bitset&
bitset&
bool

_Unchecked_set
_Unchecked_set
_Unchecked_reset
_Unchecked_flip
_Unchecked_test

(size_t
(size_t
(size_t
(size_t
(size_t

pos);
pos, int val);
pos);
pos);
pos);

Note that these may in fact be removed in the future, although we have no present plans to do so (and there doesn’t seem to be
any immediate reason to).
The member function operator[] on a const bitset returns a bool, and for a non-const bitset returns a reference (a nested
type). No range-checking is done on the index argument, in keeping with other containers’ operator[] requirements.
Finally, two additional searching functions have been added. They return the index of the first "on" bit, and the index of the first
"on" bit that is after prev, respectively:
size_t _Find_first() const;
size_t _Find_next (size_t prev) const;

The same caveat given for the _Unchecked_* functions applies here also.

23.2

Deprecated

The SGI hashing classes hash_set and hash_set have been deprecated by the unordered_set, unordered_multiset, unordered_map, unordered_multimap containers in TR1 and C++11, and may be removed in future releases.
The SGI headers

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are all here;  and  are deprecated but available as backwards-compatible
extensions, as discussed further below.  is the SGI specialization for large strings ("rope," "large strings," get it?
Love that geeky humor.)  (superseded in C++11 by ) is a singly-linked list, for when the
doubly-linked list<> is too much space overhead, and  exposes the red-black tree classes used in the
implementation of the standard maps and sets.
Each of the associative containers map, multimap, set, and multiset have a counterpart which uses a hashing function to do the
arranging, instead of a strict weak ordering function. The classes take as one of their template parameters a function object that
will return the hash value; by default, an instantiation of hash. You should specialize this functor for your class, or define your
own, before trying to use one of the hashing classes.
The hashing classes support all the usual associative container functions, as well as some extra constructors specifying the number
of buckets, etc.
Why would you want to use a hashing class instead of the “normal”implementations? Matt Austern writes:
[W]ith a well chosen hash function, hash tables generally provide much better average-case performance than binary
search trees, and much worse worst-case performance. So if your implementation has hash_map, if you don’t mind
using nonstandard components, and if you aren’t scared about the possibility of pathological cases, you’ll probably
get better performance from hash_map.
The deprecated hash tables are superseded by the standard unordered associative containers defined in the ISO C++ 2011 standard
in the headers  and .

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Chapter 24

Utilities
The  header contains many additional functors and helper functions, extending section 20.3. They are implemented in the file stl_function.h:
• identity_element for addition and multiplication.
• The functor identity, whose operator() returns the argument unchanged.
• Composition functors unary_function and binary_function, and their helpers compose1 and compose2.
• select1st and select2nd, to strip pairs.
• project1st and project2nd.
• A set of functors/functions which always return the same result. They are constant_void_fun, constant_binary_
fun, constant_unary_fun, constant0, constant1, and constant2.
• The class subtractive_rng.
• mem_fun adaptor helpers mem_fun1 and mem_fun1_ref are provided for backwards compatibility.
20.4.1 can use several different allocators; they are described on the main extensions page.
20.4.3 is extended with a special version of get_temporary_buffer taking a second argument. The argument is a pointer,
which is ignored, but can be used to specify the template type (instead of using explicit function template arguments like the
standard version does). That is, in addition to
get_temporary_buffer(5);

you can also use
get_temporary_buffer(5, (int*)0);

A class temporary_buffer is given in stl_tempbuf.h.
The specialized algorithms of section 20.4.4 are extended with uninitialized_copy_n.

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Chapter 25

Algorithms
25.1.6 (count, count_if) is extended with two more versions of count and count_if. The standard versions return their results.
The additional signatures return void, but take a final parameter by reference to which they assign their results, e.g.,
void count (first, last, value, n);

25.2 (mutating algorithms) is extended with two families of signatures, random_sample and random_sample_n.
25.2.1 (copy) is extended with
copy_n (_InputIter first, _Size count, _OutputIter result);

which copies the first ’count’ elements at ’first’ into ’result’.
25.3 (sorting ’n’ heaps ’n’ stuff) is extended with some helper predicates. Look in the doxygen-generated pages for notes on
these.
• is_heap tests whether or not a range is a heap.
• is_sorted tests whether or not a range is sorted in nondescending order.
25.3.8 (lexicographical_compare) is extended with
lexicographical_compare_3way(_InputIter1 first1, _InputIter1 last1,
_InputIter2 first2, _InputIter2 last2)

which does... what?

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Chapter 26

Numerics
26.4, the generalized numeric operations such as accumulate, are extended with the following functions:
power (x, n);
power (x, n, monoid_operation);

Returns, in FORTRAN syntax, "x ** n" where n >=0. In the case of n ==0, returns the identity element for the monoid
operation. The two-argument signature uses multiplication (for a true "power" implementation), but addition is supported as
well. The operation functor must be associative.
The iota function wins the award for Extension With the Coolest Name (the name comes from Ken Iverson’s APL language.)
As described in the SGI documentation, it "assigns sequentially increasing values to a range. That is, it assigns value to
*first, value + 1 to *(first + 1) and so on."
void iota(_ForwardIter first, _ForwardIter last, _Tp value);

The iota function is included in the ISO C++ 2011 standard.

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Chapter 27

Iterators
24.3.2 describes struct iterator, which didn’t exist in the original HP STL implementation (the language wasn’t rich
enough at the time). For backwards compatibility, base classes are provided which declare the same nested typedefs:
• input_iterator
• output_iterator
• forward_iterator
• bidirectional_iterator
• random_access_iterator
24.3.4 describes iterator operation distance, which takes two iterators and returns a result. It is extended by another signature
which takes two iterators and a reference to a result. The result is modified, and the function returns nothing.

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Chapter 28

Input and Output
Extensions allowing filebufs to be constructed from "C" types like FILE*s and file descriptors.

28.1

Derived filebufs

The v2 library included non-standard extensions to construct std::filebufs from C stdio types such as FILE*s and POSIX
file descriptors. Today the recommended way to use stdio types with libstdc++ IOStreams is via the stdio_filebuf class
(see below), but earlier releases provided slightly different mechanisms.
• 3.0.x filebufs have another ctor with this signature: basic_filebuf(__c_file_type*, ios_base::openmod
e, int_type); This comes in very handy in a number of places, such as attaching Unix sockets, pipes, and anything else
which uses file descriptors, into the IOStream buffering classes. The three arguments are as follows:
– __c_file_type* F // the __c_file_type typedef usually boils down to stdio’s FILE
– ios_base::openmode M // same as all the other uses of openmode
– int_type B // buffer size, defaults to BUFSIZ if not specified
For those wanting to use file descriptors instead of FILE*’s, I invite you to contemplate the mysteries of C’s fdopen().
• In library snapshot 3.0.95 and later, filebufs bring back an old extension: the fd() member function. The integer returned
from this function can be used for whatever file descriptors can be used for on your platform. Naturally, the library cannot
track what you do on your own with a file descriptor, so if you perform any I/O directly, don’t expect the library to be aware of
it.
• Beginning with 3.1, the extra filebuf constructor and the fd() function were removed from the standard filebuf. Instead,  contains a derived class called __gnu_cxx::stdio_filebuf. This class can be
constructed from a C FILE* or a file descriptor, and provides the fd() function.

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Chapter 29

Demangling
Transforming C++ ABI identifiers (like RTTI symbols) into the original C++ source identifiers is called “demangling.”
If you have read the source documentation for namespace abi then you are aware of the cross-vendor C++ ABI in use by
GCC. One of the exposed functions is used for demangling, abi::__cxa_demangle.
In programs like c++filt, the linker, and other tools have the ability to decode C++ ABI names, and now so can you.
(The function itself might use different demanglers, but that’s the whole point of abstract interfaces. If we change the implementation, you won’t notice.)
Probably the only times you’ll be interested in demangling at runtime are when you’re seeing typeid strings in RTTI, or when
you’re handling the runtime-support exception classes. For example:
#include 
#include 
#include 
struct empty { };
template 
struct bar { };

int main()
{
int
status;
char
*realname;
// exception classes not in , thrown by the implementation
// instead of the user
std::bad_exception e;
realname = abi::__cxa_demangle(e.what(), 0, 0, &status);
std::cout << e.what() << "\t=> " << realname << "\t: " << status << ’\n’;
free(realname);

// typeid
bar
const std::type_info

u;
&ti = typeid(u);

realname = abi::__cxa_demangle(ti.name(), 0, 0, &status);
std::cout << ti.name() << "\t=> " << realname << "\t: " << status << ’\n’;
free(realname);
return 0;
}

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This prints
St13bad_exception
3barI5emptyLi17EE

=> std::bad_exception
=> bar

: 0
: 0

The demangler interface is described in the source documentation linked to above. It is actually written in C, so you don’t need
to be writing C++ in order to demangle C++. (That also means we have to use crummy memory management facilities, so don’t
forget to free() the returned char array.)

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Chapter 30

Concurrency
30.1

Design

30.1.1

Interface to Locks and Mutexes

The file  contains all the higher-level constructs for playing with threads. In contrast to the atomics
layer, the concurrence layer consists largely of types. All types are defined within namespace __gnu_cxx.
These types can be used in a portable manner, regardless of the specific environment. They are carefully designed to provide
optimum efficiency and speed, abstracting out underlying thread calls and accesses when compiling for single-threaded situations
(even on hosts that support multiple threads.)
The enumerated type _Lock_policy details the set of available locking policies: _S_single, _S_mutex, and _S_ato
mic.
• _S_single
Indicates single-threaded code that does not need locking.
• _S_mutex
Indicates multi-threaded code using thread-layer abstractions.
• _S_atomic
Indicates multi-threaded code using atomic operations.
The compile-time constant __default_lock_policy is set to one of the three values above, depending on characteristics
of the host environment and the current compilation flags.
Two more datatypes make up the rest of the interface: __mutex, and __scoped_lock.
The scoped lock idiom is well-discussed within the C++ community. This version takes a __mutex reference, and locks it
during construction of __scoped_lock and unlocks it during destruction. This is an efficient way of locking critical sections,
while retaining exception-safety. These types have been superseded in the ISO C++ 2011 standard by the mutex and lock types
defined in the header .

30.1.2

Interface to Atomic Functions

Two functions and one type form the base of atomic support.
The type _Atomic_word is a signed integral type supporting atomic operations.
The two functions functions are:

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_Atomic_word
__exchange_and_add_dispatch(volatile _Atomic_word*, int);
void
__atomic_add_dispatch(volatile _Atomic_word*, int);

Both of these functions are declared in the header file , and are in namespace __gnu_cxx.
•

__exchange_and_add_dispatch
Adds the second argument’s value to the first argument. Returns the old value.

•

__atomic_add_dispatch
Adds the second argument’s value to the first argument. Has no return value.

These functions forward to one of several specialized helper functions, depending on the circumstances. For instance,
__exchange_and_add_dispatch
Calls through to either of:
• __exchange_and_add
Multi-thread version. Inlined if compiler-generated builtin atomics can be used, otherwise resolved at link time to a non-builtin
code sequence.
• __exchange_and_add_single
Single threaded version. Inlined.
However, only __exchange_and_add_dispatch and __atomic_add_dispatch should be used. These functions can
be used in a portable manner, regardless of the specific environment. They are carefully designed to provide optimum efficiency
and speed, abstracting out atomic accesses when they are not required (even on hosts that support compiler intrinsics for atomic
operations.)
In addition, there are two macros
_GLIBCXX_READ_MEM_BARRIER
_GLIBCXX_WRITE_MEM_BARRIER
Which expand to the appropriate write and read barrier required by the host hardware and operating system.

30.2

Implementation

30.2.1

Using Built-in Atomic Functions

The functions for atomic operations described above are either implemented via compiler intrinsics (if the underlying host is
capable) or by library fallbacks.
Compiler intrinsics (builtins) are always preferred. However, as the compiler builtins for atomics are not universally implemented,
using them directly is problematic, and can result in undefined function calls.
Prior to GCC 4.7 the older __sync intrinsics were used. An example of an undefined symbol from the use of __sync_fetc
h_and_add on an unsupported host is a missing reference to __sync_fetch_and_add_4.
Current releases use the newer __atomic intrinsics, which are implemented by library calls if the hardware doesn’t support
them. Undefined references to functions like __atomic_is_lock_free should be resolved by linking to libatomic,
which is usually installed alongside libstdc++.

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In addition, on some hosts the compiler intrinsics are enabled conditionally, via the -march command line flag. This makes
usage vary depending on the target hardware and the flags used during compile.
If builtins are possible for bool-sized integral types, ATOMIC_BOOL_LOCK_FREE will be defined. If builtins are possible for
int-sized integral types, ATOMIC_INT_LOCK_FREE will be defined.
For the following hosts, intrinsics are enabled by default.
• alpha
• ia64
• powerpc
• s390
For others, some form of -march may work. On non-ancient x86 hardware, -march=native usually does the trick.
For hosts without compiler intrinsics, but with capable hardware, hand-crafted assembly is selected. This is the case for the
following hosts:
• cris
• hppa
• i386
• i486
• m48k
• mips
• sparc
And for the rest, a simulated atomic lock via pthreads.
Detailed information about compiler intrinsics for atomic operations can be found in the GCC documentation.
More details on the library fallbacks from the porting section.

30.2.2

Thread Abstraction

A thin layer above IEEE 1003.1 (i.e. pthreads) is used to abstract the thread interface for GCC. This layer is called "gthread,"
and is comprised of one header file that wraps the host’s default thread layer with a POSIX-like interface.
The file  points to the deduced wrapper for the current host. In libstdc++ implementation files,  is
used to select the proper gthreads file.
Within libstdc++ sources, all calls to underlying thread functionality use this layer. More detail as to the specific interface can be
found in the source documentation.
By design, the gthread layer is interoperable with the types, functions, and usage found in the usual  file, including
pthread_t, pthread_once_t, pthread_create, etc.

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Use

Typical usage of the last two constructs is demonstrated as follows:
#include 
namespace
{
__gnu_cxx::__mutex safe_base_mutex;
} // anonymous namespace
namespace other
{
void
foo()
{
__gnu_cxx::__scoped_lock sentry(safe_base_mutex);
for (int i = 0; i < max; ++i)
{
_Safe_iterator_base* __old = __iter;
__iter = __iter-<_M_next;
__old-<_M_detach_single();
}
}

In this sample code, an anonymous namespace is used to keep the __mutex private to the compilation unit, and __scoped_
lock is used to guard access to the critical section within the for loop, locking the mutex on creation and freeing the mutex as
control moves out of this block.
Several exception classes are used to keep track of concurrence-related errors. These classes are: __concurrence_lock_e
rror, __concurrence_unlock_error, __concurrence_wait_error, and __concurrence_broadcast_er
ror.

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Part IV

Appendices

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Appendix A

Contributing
The GNU C++ Library is part of GCC and follows the same development model, so the general rules for contributing to GCC
apply. Active contributors are assigned maintainership responsibility, and given write access to the source repository. First-time
contributors should follow this procedure:

A.1
A.1.1

Contributor Checklist
Reading

• Get and read the relevant sections of the C++ language specification. Copies of the full ISO 14882 standard are available on
line via the ISO mirror site for committee members. Non-members, or those who have not paid for the privilege of sitting
on the committee and sustained their two meeting commitment for voting rights, may get a copy of the standard from their
respective national standards organization. In the USA, this national standards organization is ANSI. (And if you’ve already
registered with them you can buy the standard on-line.)
• The library working group bugs, and known defects, can be obtained here: http://www.open-std.org/jtc1/sc22/wg21
• Peruse the GNU Coding Standards, and chuckle when you hit the part about “Using Languages Other Than C”.
• Be familiar with the extensions that preceded these general GNU rules. These style issues for libstdc++ can be found in Coding
Style.
• And last but certainly not least, read the library-specific information found in Porting and Maintenance.

A.1.2

Assignment

See the legal prerequisites for all GCC contributions.
Historically, the libstdc++ assignment form added the following question:
“ Which Belgian comic book character is better, Tintin or Asterix, and why? ”
While not strictly necessary, humoring the maintainers and answering this question would be appreciated.
Please contact Paolo Carlini at paolo.carlini@oracle.com or Jonathan Wakely at jwakely+assign@redhat.com if you are confused
about the assignment or have general licensing questions. When requesting an assignment form from assign@gnu.org, please
CC the libstdc++ maintainers above so that progress can be monitored.

A.1.3

Getting Sources

Getting write access (look for "Write after approval")

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Submitting Patches

Every patch must have several pieces of information before it can be properly evaluated. Ideally (and to ensure the fastest possible
response from the maintainers) it would have all of these pieces:
• A description of the bug and how your patch fixes this bug. For new features a description of the feature and your implementation.
• A ChangeLog entry as plain text; see the various ChangeLog files for format and content. If you are using emacs as your editor,
simply position the insertion point at the beginning of your change and hit CX-4a to bring up the appropriate ChangeLog entry.
See--magic! Similar functionality also exists for vi.
• A testsuite submission or sample program that will easily and simply show the existing error or test new functionality.
• The patch itself. If you are accessing the SVN repository use svn update; svn diff NEW; else, use diff -cp OLD NEW ...
If your version of diff does not support these options, then get the latest version of GNU diff. The SVN Tricks wiki page has
information on customising the output of svn diff.
• When you have all these pieces, bundle them up in a mail message and send it to libstdc++@gcc.gnu.org. All patches and
related discussion should be sent to the libstdc++ mailing list. In common with the rest of GCC, patches should also be sent to
the gcc-patches mailing list.

A.2

Directory Layout and Source Conventions

The libstdc++-v3 directory in the GCC sources contains the files needed to create the GNU C++ Library.
It has subdirectories:
doc Files in HTML and text format that document usage, quirks of the implementation, and contributor checklists.
include All header files for the C++ library are within this directory, modulo specific runtime-related files that are in the
libsupc++ directory.
include/std Files meant to be found by #include  directives in standard-conforming user programs.
include/c Headers intended to directly include standard C headers. [NB: this can be enabled via --enable-chead
ers=c]
include/c_global Headers intended to include standard C headers in the global namespace, and put select names
into the std:: namespace. [NB: this is the default, and is the same as --enable-cheaders=c_global]
include/c_std Headers intended to include standard C headers already in namespace std, and put select names into
the std:: namespace. [NB: this is the same as --enable-cheaders=c_std]
include/bits Files included by standard headers and by other files in the bits directory.
include/backward Headers provided for backward compatibility, such as . They are not
used in this library.
include/ext Headers that define extensions to the standard library. No standard header refers to any of them, in theory
(there are some exceptions).
include/debug, include/parallel, and include/profile Headers that implement the Debug Mode, Parallel Mode, and Profile Mode extensions.
scripts Scripts that are used during the configure, build, make, or test process.
src Files that are used in constructing the library, but are not installed.
src/c++98 Source files compiled using -std=gnu++98.
src/c++11 Source files compiled using -std=gnu++11.
src/filesystem Source files for the Filesystem TS.

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src/shared Source code included by other files under both src/c++98 and src/c++11
testsuites/[backward, demangle, ext, performance, thread, 17_* to 30_*] Test programs are here,
and may be used to begin to exercise the library. Support for "make check" and "make check-install" is complete, and runs
through all the subdirectories here when this command is issued from the build directory. Please note that "make check"
requires DejaGnu 1.4 or later to be installed, or for extra permutations DejaGnu 1.5.3 or later.
Other subdirectories contain variant versions of certain files that are meant to be copied or linked by the configure script. Currently
these are:
config/abi
config/allocator
config/cpu
config/io
config/locale
config/os
In addition, a subdirectory holds the convenience library libsupc++.
libsupc++ Contains the runtime library for C++, including exception handling and memory allocation and deallocation,
RTTI, terminate handlers, etc.
Note that glibc also has a bits/ subdirectory. We need to be careful not to collide with names in its bits/ directory. For
example  has to be renamed from . Another solution would be to rename bits
to (e.g.) cppbits.
In files throughout the system, lines marked with an "XXX" indicate a bug or incompletely-implemented feature. Lines marked
"XXX MT" indicate a place that may require attention for multi-thread safety.

A.3

Coding Style

A.3.1

Bad Identifiers

Identifiers that conflict and should be avoided.
This is the list of names reserved to the
implementation that have been claimed by certain
compilers and system headers of interest, and should not be used
in the library. It will grow, of course. We generally are
interested in names that are not all-caps, except for those like
"_T"
For Solaris:
_B
_C
_L
_N
_P
_S
_U
_X
_E1
..
_E24
Irix adds:

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_A
_G
MS adds:
_T
BSD adds:
__used
__unused
__inline
_Complex
__istype
__maskrune
__tolower
__toupper
__wchar_t
__wint_t
_res
_res_ext
__tg_*
SPU adds:
__ea
For GCC:
[Note that this list is out of date. It applies to the old
name-mangling; in G++ 3.0 and higher a different name-mangling is
used. In addition, many of the bugs relating to G++ interpreting
these names as operators have been fixed.]
The full set of __* identifiers (combined from gcc/cp/lex.c and
gcc/cplus-dem.c) that are either old or new, but are definitely
recognized by the demangler, is:
__aa
__aad
__ad
__addr
__adv
__aer
__als
__alshift
__amd
__ami
__aml
__amu
__aor
__apl
__array
__ars
__arshift
__as
__bit_and
__bit_ior
__bit_not
__bit_xor

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__call
__cl
__cm
__cn
__co
__component
__compound
__cond
__convert
__delete
__dl
__dv
__eq
__er
__ge
__gt
__indirect
__le
__ls
__lt
__max
__md
__method_call
__mi
__min
__minus
__ml
__mm
__mn
__mult
__mx
__ne
__negate
__new
__nop
__nt
__nw
__oo
__op
__or
__pl
__plus
__postdecrement
__postincrement
__pp
__pt
__rf
__rm
__rs
__sz
__trunc_div
__trunc_mod
__truth_andif
__truth_not
__truth_orif
__vc
__vd

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__vn
SGI badnames:
__builtin_alloca
__builtin_fsqrt
__builtin_sqrt
__builtin_fabs
__builtin_dabs
__builtin_cast_f2i
__builtin_cast_i2f
__builtin_cast_d2ll
__builtin_cast_ll2d
__builtin_copy_dhi2i
__builtin_copy_i2dhi
__builtin_copy_dlo2i
__builtin_copy_i2dlo
__add_and_fetch
__sub_and_fetch
__or_and_fetch
__xor_and_fetch
__and_and_fetch
__nand_and_fetch
__mpy_and_fetch
__min_and_fetch
__max_and_fetch
__fetch_and_add
__fetch_and_sub
__fetch_and_or
__fetch_and_xor
__fetch_and_and
__fetch_and_nand
__fetch_and_mpy
__fetch_and_min
__fetch_and_max
__lock_test_and_set
__lock_release
__lock_acquire
__compare_and_swap
__synchronize
__high_multiply
__unix
__sgi
__linux__
__i386__
__i486__
__cplusplus
__embedded_cplusplus
// long double conversion members mangled as __opr
// http://gcc.gnu.org/ml/libstdc++/1999-q4/msg00060.html
__opr

A.3.2

By Example
This library is written to appropriate C++ coding standards. As such,
it is intended to precede the recommendations of the GNU Coding

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Standard, which can be referenced in full here:
http://www.gnu.org/prep/standards/standards.html#Formatting
The rest of this is also interesting reading, but skip the "Design
Advice" part.
The GCC coding conventions are here, and are also useful:
http://gcc.gnu.org/codingconventions.html
In addition, because it doesn’t seem to be stated explicitly anywhere
else, there is an 80 column source limit.
ChangeLog entries for member functions should use the
classname::member function name syntax as follows:

1999-04-15

Dennis Ritchie



* src/basic_file.cc (__basic_file::open): Fix thinko in
_G_HAVE_IO_FILE_OPEN bits.

Notable areas of divergence from what may be previous local practice
(particularly for GNU C) include:
01. Pointers and references
char* p
char& c
-NOTchar *p
char &c

= "flop";
= *p;
= "flop";
= *p;

// wrong
// wrong

Reason: In C++, definitions are mixed with executable code. Here,
p is being initialized, not *p. This is near-universal
practice among C++ programmers; it is normal for C hackers
to switch spontaneously as they gain experience.
02. Operator names and parentheses
operator==(type)
-NOToperator == (type)

// wrong

Reason: The == is part of the function name. Separating
it makes the declaration look like an expression.
03. Function names and parentheses
void mangle()
-NOTvoid mangle ()

// wrong

The GNU C++ Library Manual

Reason: no space before parentheses (except after a control-flow
keyword) is near-universal practice for C++. It identifies the
parentheses as the function-call operator or declarator, as
opposed to an expression or other overloaded use of parentheses.
04. Template function indentation
template
void
template_function(args)
{ }
-NOTtemplate
void template_function(args) {};

Reason: In class definitions, without indentation whitespace is
needed both above and below the declaration to distinguish
it visually from other members. (Also, re: "typename"
rather than "class".) T often could be int, which is
not a class. ("class", here, is an anachronism.)
05. Template class indentation
template
class basic_ios : public ios_base
{
public:
// Types:
};
-NOTtemplate
class basic_ios : public ios_base
{
public:
// Types:
};
-NOTtemplate
class basic_ios : public ios_base
{
public:
// Types:
};

06. Enumerators
enum
{
space = _ISspace,
print = _ISprint,
cntrl = _IScntrl
};
-NOTenum { space = _ISspace, print = _ISprint, cntrl = _IScntrl };

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07. Member initialization lists
All one line, separate from class name.

gribble::gribble()
: _M_private_data(0), _M_more_stuff(0), _M_helper(0)
{ }
-NOTgribble::gribble() : _M_private_data(0), _M_more_stuff(0), _M_helper(0)
{ }

08. Try/Catch blocks
try
{
//
}
catch (...)
{
//
}
-NOTtry {
//
} catch(...) {
//
}

09. Member functions declarations and definitions
Keywords such as extern, static, export, explicit, inline, etc
go on the line above the function name. Thus

virtual int
foo()
-NOTvirtual int foo()

Reason: GNU coding conventions dictate return types for functions
are on a separate line than the function name and parameter list
for definitions. For C++, where we have member functions that can
be either inline definitions or declarations, keeping to this
standard allows all member function names for a given class to be
aligned to the same margin, increasing readability.

10. Invocation of member functions with "this->"
For non-uglified names, use this->name to call the function.

this->sync()
-NOTsync()

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Reason: Koenig lookup.
11. Namespaces
namespace std
{
blah blah blah;
} // namespace std
-NOTnamespace std {
blah blah blah;
} // namespace std

12. Spacing under protected and private in class declarations:
space above, none below
i.e.

public:
int foo;
-NOTpublic:
int foo;

13. Spacing WRT return statements.
no extra spacing before returns, no parenthesis
i.e.

}
return __ret;
-NOT}
return __ret;
-NOT}
return (__ret);

14. Location of global variables.
All global variables of class type, whether in the "user visible"
space (e.g., cin) or the implementation namespace, must be defined
as a character array with the appropriate alignment and then later
re-initialized to the correct value.

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This is due to startup issues on certain platforms, such as AIX.
For more explanation and examples, see src/globals.cc. All such
variables should be contained in that file, for simplicity.
15. Exception abstractions
Use the exception abstractions found in functexcept.h, which allow
C++ programmers to use this library with -fno-exceptions. (Even if
that is rarely advisable, it’s a necessary evil for backwards
compatibility.)
16. Exception error messages
All start with the name of the function where the exception is
thrown, and then (optional) descriptive text is added. Example:

__throw_logic_error(__N("basic_string::_S_construct NULL not valid"));

Reason: The verbose terminate handler prints out exception::what(),
as well as the typeinfo for the thrown exception. As this is the
default terminate handler, by putting location info into the
exception string, a very useful error message is printed out for
uncaught exceptions. So useful, in fact, that non-programmers can
give useful error messages, and programmers can intelligently
speculate what went wrong without even using a debugger.
17. The doxygen style guide to comments is a separate document,
see index.
The library currently has a mixture of GNU-C and modern C++ coding
styles. The GNU C usages will be combed out gradually.
Name patterns:
For nonstandard names appearing in Standard headers, we are constrained
to use names that begin with underscores. This is called "uglification".
The convention is:
Local and argument names:
Examples:

__count

__ix

__[a-z].*
__s1

Type names and template formal-argument names: _[A-Z][^_].*
Examples:

_Helper

_CharT

_N

Member data and function names: _M_.*
Examples:

_M_num_elements

_M_initialize ()

Static data members, constants, and enumerations: _S_.*
Examples: _S_max_elements

_S_default_value

Don’t use names in the same scope that differ only in the prefix,
e.g. _S_top and _M_top. See BADNAMES for a list of forbidden names.

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(The most tempting of these seem to be and "_T" and "__sz".)
Names must never have "__" internally; it would confuse name
unmanglers on some targets. Also, never use "__[0-9]", same reason.
-------------------------[BY EXAMPLE]

#ifndef
#define

_HEADER_
_HEADER_ 1

namespace std
{
class gribble
{
public:
gribble() throw();
gribble(const gribble&);
explicit
gribble(int __howmany);
gribble&
operator=(const gribble&);
virtual
~gribble() throw ();
// Start with a capital letter, end with a period.
inline void
public_member(const char* __arg) const;
// In-class function definitions should be restricted to one-liners.
int
one_line() { return 0 }
int
two_lines(const char* arg)
{ return strchr(arg, ’a’); }
inline int
three_lines();

// inline, but defined below.

// Note indentation.
template
void
public_template() const throw();
template
void
other_template();
private:
class _Helper;

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int _M_private_data;
int _M_more_stuff;
_Helper* _M_helper;
int _M_private_function();
enum _Enum
{
_S_one,
_S_two
};
static void
_S_initialize_library();
};
// More-or-less-standard language features described by lack, not presence ←.
# ifndef _G_NO_LONGLONG
extern long long _G_global_with_a_good_long_name; // avoid globals!
# endif
// Avoid in-class inline definitions, define separately;
// likewise for member class definitions:
inline int
gribble::public_member() const
{ int __local = 0; return __local; }
class gribble::_Helper
{
int _M_stuff;
friend class gribble;
};
}
// Names beginning with "__": only for arguments and
//
local variables; never use "__" in a type name, or
//
within any name; never use "__[0-9]".
#endif /* _HEADER_ */

namespace std
{
template // notice: "typename", not "class", no space
long_return_value_type
function_name(char* pointer,
// "char *pointer" is wrong.
char* argument,
const Reference& ref)
{
// int a_local; /* wrong; see below. */
if (test)
{
nested code
}

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int a_local = 0;

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// declare variable at first use.

// char a, b, *p;
/* wrong */
char a = ’a’;
char b = a + 1;
char* c = "abc"; // each variable goes on its own line, always.
// except maybe here...
for (unsigned i = 0, mask = 1; mask; ++i, mask <<= 1) {
// ...
}
}
gribble::gribble()
: _M_private_data(0), _M_more_stuff(0), _M_helper(0)
{ }
int
gribble::three_lines()
{
// doesn’t fit in one line.
}
} // namespace std

A.4

Design Notes
The Library
----------This paper is covers two major areas:
- Features and policies not mentioned in the standard that
the quality of the library implementation depends on, including
extensions and "implementation-defined" features;
- Plans for required but unimplemented library features and
optimizations to them.
Overhead
-------The standard defines a large library, much larger than the standard
C library. A naive implementation would suffer substantial overhead
in compile time, executable size, and speed, rendering it unusable
in many (particularly embedded) applications. The alternative demands
care in construction, and some compiler support, but there is no
need for library subsets.
What are the sources of this overhead?

There are four main causes:

- The library is specified almost entirely as templates, which
with current compilers must be included in-line, resulting in
very slow builds as tens or hundreds of thousands of lines

The GNU C++ Library Manual

of function definitions are read for each user source file.
Indeed, the entire SGI STL, as well as the dos Reis valarray,
are provided purely as header files, largely for simplicity in
porting. Iostream/locale is (or will be) as large again.
- The library is very flexible, specifying a multitude of hooks
where users can insert their own code in place of defaults.
When these hooks are not used, any time and code expended to
support that flexibility is wasted.
- Templates are often described as causing to "code bloat". In
practice, this refers (when it refers to anything real) to several
independent processes. First, when a class template is manually
instantiated in its entirely, current compilers place the definitions
for all members in a single object file, so that a program linking
to one member gets definitions of all. Second, template functions
which do not actually depend on the template argument are, under
current compilers, generated anew for each instantiation, rather
than being shared with other instantiations. Third, some of the
flexibility mentioned above comes from virtual functions (both in
regular classes and template classes) which current linkers add
to the executable file even when they manifestly cannot be called.
- The library is specified to use a language feature, exceptions,
which in the current gcc compiler ABI imposes a run time and
code space cost to handle the possibility of exceptions even when
they are not used. Under the new ABI (accessed with -fnew-abi),
there is a space overhead and a small reduction in code efficiency
resulting from lost optimization opportunities associated with
non-local branches associated with exceptions.
What can be done to eliminate this overhead? A variety of coding
techniques, and compiler, linker and library improvements and
extensions may be used, as covered below. Most are not difficult,
and some are already implemented in varying degrees.
Overhead: Compilation Time
-------------------------Providing "ready-instantiated" template code in object code archives
allows us to avoid generating and optimizing template instantiations
in each compilation unit which uses them. However, the number of such
instantiations that are useful to provide is limited, and anyway this
is not enough, by itself, to minimize compilation time. In particular,
it does not reduce time spent parsing conforming headers.
Quicker header parsing will depend on library extensions and compiler
improvements. One approach is some variation on the techniques
previously marketed as "pre-compiled headers", now standardized as
support for the "export" keyword. "Exported" template definitions
can be placed (once) in a "repository" -- really just a library, but
of template definitions rather than object code -- to be drawn upon
at link time when an instantiation is needed, rather than placed in
header files to be parsed along with every compilation unit.
Until "export" is implemented we can put some of the lengthy template
definitions in #if guards or alternative headers so that users can skip

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over the full definitions when they need only the ready-instantiated
specializations.
To be precise, this means that certain headers which define
templates which users normally use only for certain arguments
can be instrumented to avoid exposing the template definitions
to the compiler unless a macro is defined. For example, in
, we might have:
template  class basic_string {
... // member declarations
};
... // operator declarations
#ifdef _STRICT_ISO_
# if _G_NO_TEMPLATE_EXPORT
#
include  // headers needed by definitions
#
...
#
include  // member and global template definitions.
# endif
#endif
Users who compile without specifying a strict-ISO-conforming flag
would not see many of the template definitions they now see, and rely
instead on ready-instantiated specializations in the library. This
technique would be useful for the following substantial components:
string, locale/iostreams, valarray. It would *not* be useful or
usable with the following: containers, algorithms, iterators,
allocator. Since these constitute a large (though decreasing)
fraction of the library, the benefit the technique offers is
limited.
The language specifies the semantics of the "export" keyword, but
the gcc compiler does not yet support it. When it does, problems
with large template inclusions can largely disappear, given some
minor library reorganization, along with the need for the apparatus
described above.
Overhead: Flexibility Cost
-------------------------The library offers many places where users can specify operations
to be performed by the library in place of defaults. Sometimes
this seems to require that the library use a more-roundabout, and
possibly slower, way to accomplish the default requirements than
would be used otherwise.
The primary protection against this overhead is thorough compiler
optimization, to crush out layers of inline function interfaces.
Kuck & Associates has demonstrated the practicality of this kind
of optimization.
The second line of defense against this overhead is explicit
specialization. By defining helper function templates, and writing
specialized code for the default case, overhead can be eliminated
for that case without sacrificing flexibility. This takes full
advantage of any ability of the optimizer to crush out degenerate

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code.
The library specifies many virtual functions which current linkers
load even when they cannot be called. Some minor improvements to the
compiler and to ld would eliminate any such overhead by simply
omitting virtual functions that the complete program does not call.
A prototype of this work has already been done. For targets where
GNU ld is not used, a "pre-linker" could do the same job.
The main areas in the standard interface where user flexibility
can result in overhead are:
- Allocators: Containers are specified to use user-definable
allocator types and objects, making tuning for the container
characteristics tricky.
- Locales: the standard specifies locale objects used to implement
iostream operations, involving many virtual functions which use
streambuf iterators.
- Algorithms and containers: these may be instantiated on any type,
frequently duplicating code for identical operations.
- Iostreams and strings: users are permitted to use these on their
own types, and specify the operations the stream must use on these
types.
Note that these sources of overhead are _avoidable_. The techniques
to avoid them are covered below.
Code Bloat
---------In the SGI STL, and in some other headers, many of the templates
are defined "inline" -- either explicitly or by their placement
in class definitions -- which should not be inline. This is a
source of code bloat. Matt had remarked that he was relying on
the compiler to recognize what was too big to benefit from inlining,
and generate it out-of-line automatically. However, this also can
result in code bloat except where the linker can eliminate the extra
copies.
Fixing these cases will require an audit of all inline functions
defined in the library to determine which merit inlining, and moving
the rest out of line. This is an issue mainly in clauses 23, 25, and
27. Of course it can be done incrementally, and we should generally
accept patches that move large functions out of line and into ".tcc"
files, which can later be pulled into a repository. Compiler/linker
improvements to recognize very large inline functions and move them
out-of-line, but shared among compilation units, could make this
work unnecessary.
Pre-instantiating template specializations currently produces large
amounts of dead code which bloats statically linked programs. The
current state of the static library, libstdc++.a, is intolerable on
this account, and will fuel further confused speculation about a need
for a library "subset". A compiler improvement that treats each

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instantiated function as a separate object file, for linking purposes,
would be one solution to this problem. An alternative would be to
split up the manual instantiation files into dozens upon dozens of
little files, each compiled separately, but an abortive attempt at
this was done for  and, though it is far from complete, it
is already a nuisance. A better interim solution (just until we have
"export") is badly needed.
When building a shared library, the current compiler/linker cannot
automatically generate the instantiations needed. This creates a
miserable situation; it means any time something is changed in the
library, before a shared library can be built someone must manually
copy the declarations of all templates that are needed by other parts
of the library to an "instantiation" file, and add it to the build
system to be compiled and linked to the library. This process is
readily automated, and should be automated as soon as possible.
Users building their own shared libraries experience identical
frustrations.
Sharing common aspects of template definitions among instantiations
can radically reduce code bloat. The compiler could help a great
deal here by recognizing when a function depends on nothing about
a template parameter, or only on its size, and giving the resulting
function a link-name "equate" that allows it to be shared with other
instantiations. Implementation code could take advantage of the
capability by factoring out code that does not depend on the template
argument into separate functions to be merged by the compiler.
Until such a compiler optimization is implemented, much can be done
manually (if tediously) in this direction. One such optimization is
to derive class templates from non-template classes, and move as much
implementation as possible into the base class. Another is to partialspecialize certain common instantiations, such as vector, to share
code for instantiations on all types T. While these techniques work,
they are far from the complete solution that a compiler improvement
would afford.
Overhead: Expensive Language Features
------------------------------------The main "expensive" language feature used in the standard library
is exception support, which requires compiling in cleanup code with
static table data to locate it, and linking in library code to use
the table. For small embedded programs the amount of such library
code and table data is assumed by some to be excessive. Under the
"new" ABI this perception is generally exaggerated, although in some
cases it may actually be excessive.
To implement a library which does not use exceptions directly is
not difficult given minor compiler support (to "turn off" exceptions
and ignore exception constructs), and results in no great library
maintenance difficulties. To be precise, given "-fno-exceptions",
the compiler should treat "try" blocks as ordinary blocks, and
"catch" blocks as dead code to ignore or eliminate. Compiler
support is not strictly necessary, except in the case of "function
try blocks"; otherwise the following macros almost suffice:

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#define throw(X)
#define try
if (true)
#define catch(X) else if (false)
However, there may be a need to use function try blocks in the
library implementation, and use of macros in this way can make
correct diagnostics impossible. Furthermore, use of this scheme
would require the library to call a function to re-throw exceptions
from a try block. Implementing the above semantics in the compiler
is preferable.
Given the support above (however implemented) it only remains to
replace code that "throws" with a call to a well-documented "handler"
function in a separate compilation unit which may be replaced by
the user. The main source of exceptions that would be difficult
for users to avoid is memory allocation failures, but users can
define their own memory allocation primitives that never throw.
Otherwise, the complete list of such handlers, and which library
functions may call them, would be needed for users to be able to
implement the necessary substitutes. (Fortunately, they have the
source code.)
Opportunities
------------The template capabilities of C++ offer enormous opportunities for
optimizing common library operations, well beyond what would be
considered "eliminating overhead". In particular, many operations
done in Glibc with macros that depend on proprietary language
extensions can be implemented in pristine Standard C++. For example,
the chapter 25 algorithms, and even C library functions such as strchr,
can be specialized for the case of static arrays of known (small) size.
Detailed optimization opportunities are identified below where
the component where they would appear is discussed. Of course new
opportunities will be identified during implementation.
Unimplemented Required Library Features
--------------------------------------The standard specifies hundreds of components, grouped broadly by
chapter. These are listed in excruciating detail in the CHECKLIST
file.
17 general
18 support
19 diagnostics
20 utilities
21 string
22 locale
23 containers
24 iterators
25 algorithms
26 numerics
27 iostreams
Annex D backward compatibility

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Anyone participating in implementation of the library should obtain
a copy of the standard, ISO 14882. People in the U.S. can obtain an
electronic copy for US$18 from ANSI’s web site. Those from other
countries should visit http://www.iso.org/ to find out the location
of their country’s representation in ISO, in order to know who can
sell them a copy.
The emphasis in the following sections is on unimplemented features
and optimization opportunities.
Chapter 17 General
------------------Chapter 17 concerns overall library requirements.
The standard doesn’t mention threads. A multi-thread (MT) extension
primarily affects operators new and delete (18), allocator (20),
string (21), locale (22), and iostreams (27). The common underlying
support needed for this is discussed under chapter 20.
The standard requirements on names from the C headers create a
lot of work, mostly done. Names in the C headers must be visible
in the std:: and sometimes the global namespace; the names in the
two scopes must refer to the same object. More stringent is that
Koenig lookup implies that any types specified as defined in std::
really are defined in std::. Names optionally implemented as
macros in C cannot be macros in C++. (An overview may be read at
). The scripts "inclosure"
and "mkcshadow", and the directories shadow/ and cshadow/, are the
beginning of an effort to conform in this area.
A correct conforming definition of C header names based on underlying
C library headers, and practical linking of conforming namespaced
customer code with third-party C libraries depends ultimately on
an ABI change, allowing namespaced C type names to be mangled into
type names as if they were global, somewhat as C function names in a
namespace, or C++ global variable names, are left unmangled. Perhaps
another "extern" mode, such as ’extern "C-global"’ would be an
appropriate place for such type definitions. Such a type would
affect mangling as follows:
namespace A {
struct X {};
extern "C-global" { // or maybe just ’extern "C"’
struct Y {};
};
}
void f(A::X*); // mangles to f__FPQ21A1X
void f(A::Y*); // mangles to f__FP1Y
(It may be that this is really the appropriate semantics for regular
’extern "C"’, and ’extern "C-global"’, as an extension, would not be
necessary.) This would allow functions declared in non-standard C headers
(and thus fixable by neither us nor users) to link properly with functions
declared using C types defined in properly-namespaced headers. The
problem this solves is that C headers (which C++ programmers do persist
in using) frequently forward-declare C struct tags without including

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the header where the type is defined, as in
struct tm;
void munge(tm*);
Without some compiler accommodation, munge cannot be called by correct
C++ code using a pointer to a correctly-scoped tm* value.
The current C headers use the preprocessor extension "#include_next",
which the compiler complains about when run "-pedantic".
(Incidentally, it appears that "-fpedantic" is currently ignored,
probably a bug.) The solution in the C compiler is to use
"-isystem" rather than "-I", but unfortunately in g++ this seems
also to wrap the whole header in an ’extern "C"’ block, so it’s
unusable for C++ headers. The correct solution appears to be to
allow the various special include-directory options, if not given
an argument, to affect subsequent include-directory options additively,
so that if one said
-pedantic -iprefix $(prefix) \
-idirafter -ino-pedantic -ino-extern-c -iwithprefix -I g++-v3 \
-iwithprefix -I g++-v3/ext
the compiler would search $(prefix)/g++-v3 and not report
pedantic warnings for files found there, but treat files in
$(prefix)/g++-v3/ext pedantically. (The undocumented semantics
of "-isystem" in g++ stink. Can they be rescinded? If not it
must be replaced with something more rationally behaved.)
All the C headers need the treatment above; in the standard these
headers are mentioned in various clauses. Below, I have only
mentioned those that present interesting implementation issues.
The components identified as "mostly complete", below, have not been
audited for conformance. In many cases where the library passes
conformance tests we have non-conforming extensions that must be
wrapped in #if guards for "pedantic" use, and in some cases renamed
in a conforming way for continued use in the implementation regardless
of conformance flags.
The STL portion of the library still depends on a header
stl/bits/stl_config.h full of #ifdef clauses. This apparatus
should be replaced with autoconf/automake machinery.
The SGI STL defines a type_traits<> template, specialized for
many types in their code including the built-in numeric and
pointer types and some library types, to direct optimizations of
standard functions. The SGI compiler has been extended to generate
specializations of this template automatically for user types,
so that use of STL templates on user types can take advantage of
these optimizations. Specializations for other, non-STL, types
would make more optimizations possible, but extending the gcc
compiler in the same way would be much better. Probably the next
round of standardization will ratify this, but probably with
changes, so it probably should be renamed to place it in the
implementation namespace.

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The SGI STL also defines a large number of extensions visible in
standard headers. (Other extensions that appear in separate headers
have been sequestered in subdirectories ext/ and backward/.) All
these extensions should be moved to other headers where possible,
and in any case wrapped in a namespace (not std!), and (where kept
in a standard header) girded about with macro guards. Some cannot be
moved out of standard headers because they are used to implement
standard features. The canonical method for accommodating these
is to use a protected name, aliased in macro guards to a user-space
name. Unfortunately C++ offers no satisfactory template typedef
mechanism, so very ad-hoc and unsatisfactory aliasing must be used
instead.
Implementation of a template typedef mechanism should have the highest
priority among possible extensions, on the same level as implementation
of the template "export" feature.
Chapter 18 Language support
---------------------------Headers:    
C headers:     

  (also 21, 25, 26)
This defines the built-in exceptions, rtti, numeric_limits<>,
operator new and delete. Much of this is provided by the
compiler in its static runtime library.
Work to do includes defining numeric_limits<> specializations in
separate files for all target architectures. Values for integer types
except for bool and wchar_t are readily obtained from the C header
, but values for the remaining numeric types (bool, wchar_t,
float, double, long double) must be entered manually. This is
largely dog work except for those members whose values are not
easily deduced from available documentation. Also, this involves
some work in target configuration to identify the correct choice of
file to build against and to install.
The definitions of the various operators new and delete must be
made thread-safe, which depends on a portable exclusion mechanism,
discussed under chapter 20. Of course there is always plenty of
room for improvements to the speed of operators new and delete.
, in Glibc, defines some macros that gcc does not allow to
be wrapped into an inline function. Probably this header will demand
attention whenever a new target is chosen. The functions atexit(),
exit(), and abort() in cstdlib have different semantics in C++, so
must be re-implemented for C++.
Chapter 19 Diagnostics
----------------------Headers: 
C headers:  
This defines the standard exception objects, which are "mostly complete".
Cygnus has a version, and now SGI provides a slightly different one.

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It makes little difference which we use.
The C global name "errno", which C allows to be a variable or a macro,
is required in C++ to be a macro. For MT it must typically result in
a function call.
Chapter 20 Utilities
--------------------Headers:   
C header:  (also in 18)
SGI STL provides "mostly complete" versions of all the components
defined in this chapter. However, the auto_ptr<> implementation
is known to be wrong. Furthermore, the standard definition of it
is known to be unimplementable as written. A minor change to the
standard would fix it, and auto_ptr<> should be adjusted to match.
Multi-threading affects the allocator implementation, and there must
be configuration/installation choices for different users’ MT
requirements. Anyway, users will want to tune allocator options
to support different target conditions, MT or no.
The primitives used for MT implementation should be exposed, as an
extension, for users’ own work. We need cross-CPU "mutex" support,
multi-processor shared-memory atomic integer operations, and singleprocessor uninterruptible integer operations, and all three configurable
to be stubbed out for non-MT use, or to use an appropriately-loaded
dynamic library for the actual runtime environment, or statically
compiled in for cases where the target architecture is known.
Chapter 21 String
-----------------Headers: 
C headers:     (also in 27)
 (also in 18, 25, 26)
We have "mostly-complete" char_traits<> implementations. Many of the
char_traits operations might be optimized further using existing
proprietary language extensions.
We have a "mostly-complete" basic_string<> implementation. The work
to manually instantiate char and wchar_t specializations in object
files to improve link-time behavior is extremely unsatisfactory,
literally tripling library-build time with no commensurate improvement
in static program link sizes. It must be redone. (Similar work is
needed for some components in clauses 22 and 27.)
Other work needed for strings is MT-safety, as discussed under the
chapter 20 heading.
The standard C type mbstate_t from  and used in char_traits<>
must be different in C++ than in C, because in C++ the default constructor
value mbstate_t() must be the "base" or "ground" sequence state.
(According to the likely resolution of a recently raised Core issue,
this may become unnecessary. However, there are other reasons to
use a state type not as limited as whatever the C library provides.)
If we might want to provide conversions from (e.g.) internally-

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represented EUC-wide to externally-represented Unicode, or viceversa, the mbstate_t we choose will need to be more accommodating
than what might be provided by an underlying C library.
There remain some basic_string template-member functions which do
not overload properly with their non-template brethren. The infamous
hack akin to what was done in vector<> is needed, to conform to
23.1.1 para 10. The CHECKLIST items for basic_string marked ’X’,
or incomplete, are so marked for this reason.
Replacing the string iterators, which currently are simple character
pointers, with class objects would greatly increase the safety of the
client interface, and also permit a "debug" mode in which range,
ownership, and validity are rigorously checked. The current use of
raw pointers as string iterators is evil. vector<> iterators need the
same treatment. Note that the current implementation freely mixes
pointers and iterators, and that must be fixed before safer iterators
can be introduced.
Some of the functions in  are different from the C version.
generally overloaded on const and non-const argument pointers. For
example, in  strchr is overloaded. The functions isupper
etc. in  typically implemented as macros in C are functions
in C++, because they are overloaded with others of the same name
defined in .
Many of the functions required in  and  cannot be
implemented using underlying C facilities on intended targets because
such facilities only partly exist.
Chapter 22 Locale
-----------------Headers: 
C headers: 
We have a "mostly complete" class locale, with the exception of
code for constructing, and handling the names of, named locales.
The ways that locales are named (particularly when categories
(e.g. LC_TIME, LC_COLLATE) are different) varies among all target
environments. This code must be written in various versions and
chosen by configuration parameters.
Members of many of the facets defined in  are stubs. Generally,
there are two sets of facets: the base class facets (which are supposed
to implement the "C" locale) and the "byname" facets, which are supposed
to read files to determine their behavior. The base ctype<>, collate<>,
and numpunct<> facets are "mostly complete", except that the table of
bitmask values used for "is" operations, and corresponding mask values,
are still defined in libio and just included/linked. (We will need to
implement these tables independently, soon, but should take advantage
of libio where possible.) The num_put<>::put members for integer types
are "mostly complete".
A complete list of what has and has not been implemented may be
found in CHECKLIST. However, note that the current definition of
codecvt is wrong. It should simply write
out the raw bytes representing the wide characters, rather than

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trying to convert each to a corresponding single "char" value.
Some of the facets are more important than others. Specifically,
the members of ctype<>, numpunct<>, num_put<>, and num_get<> facets
are used by other library facilities defined in , ,
and , and the codecvt<> facet is used by basic_filebuf<>
in , so a conforming iostream implementation depends on
these.
The "long long" type eventually must be supported, but code mentioning
it should be wrapped in #if guards to allow pedantic-mode compiling.
Performance of num_put<> and num_get<> depend critically on
caching computed values in ios_base objects, and on extensions
to the interface with streambufs.
Specifically: retrieving a copy of the locale object, extracting
the needed facets, and gathering data from them, for each call to
(e.g.) operator<< would be prohibitively slow. To cache format
data for use by num_put<> and num_get<> we have a _Format_cache<>
object stored in the ios_base::pword() array. This is constructed
and initialized lazily, and is organized purely for utility. It
is discarded when a new locale with different facets is imbued.
Using only the public interfaces of the iterator arguments to the
facet functions would limit performance by forbidding "vector-style"
character operations. The streambuf iterator optimizations are
described under chapter 24, but facets can also bypass the streambuf
iterators via explicit specializations and operate directly on the
streambufs, and use extended interfaces to get direct access to the
streambuf internal buffer arrays. These extensions are mentioned
under chapter 27. These optimizations are particularly important
for input parsing.
Unused virtual members of locale facets can be omitted, as mentioned
above, by a smart linker.
Chapter 23 Containers
---------------------Headers:      
blocks and @code/@endcode sections, spacing can have “interesting” effects.
Use either kind of grouping, as appropriate. doxygroups.cc exists for this purpose. See stl_iterator.h for a good
example of the “other” kind of grouping.
Please use markup tags like @p and @a when referring to things such as the names of function parameters. Use @e for emphasis
when necessary. Use @c to refer to other standard names. (Examples of all these abound in the present code.)
Complicated math functions should use the multi-line format. An example from random.h:
/**
* @brief A model of a linear congruential random number generator.
*
* @f[
x_{i+1}\leftarrow(ax_{i} + c) \bmod m
*
@f]
*
*/
One area of note is the markup required for @file markup in header files. Two details are important: for filenames that have
the same name in multiple directories, include part of the installed path to disambiguate. For example:
/** @file debug/vector
* This file is a GNU debug extension to the Standard C++ Library.
*/
The other relevant detail for header files is the use of a libstdc++-specific doxygen alias that helps distinguish between public
header files (like random) from implementation or private header files (like bits/c++config.h.) This alias is spelled @
headername and can take one or two arguments that detail the public header file or files that should be included to use the
contents of the file. All header files that are not intended for direct inclusion must use headername in the file block. An
example:
/** @file bits/basic_string.h
* This is an internal header file, included by other library headers.
* Do not attempt to use it directly. @headername{string}
*/
Be careful about using certain, special characters when writing Doxygen comments. Single and double quotes, and separators in
filenames are two common trouble spots. When in doubt, consult the following table.

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HTML
\
"
’






Doxygen
\\
\"
\’
@a word
@b word
@c word
@a word
two words or more
Table B.2: HTML to Doxygen Markup Comparison

B.2.4

Docbook

B.2.4.1

Prerequisites

Tool
docbook5-style-xsl
xsltproc
xmllint
dblatex
pdflatex
docbook2X
epub3 stylesheets

Version
1.76.1
1.1.26
2.7.7
0.3
2007-59
0.8.8
b3

Required By
all
all
validation
pdf output
pdf output
info output
epub output

Table B.3: Docbook Prerequisites
Editing the DocBook sources requires an XML editor. Many exist: some notable options include emacs, Kate, or Conglomerate.
Some editors support special “XML Validation” modes that can validate the file as it is produced. Recommended is the nXML
Mode for emacs.
Besides an editor, additional DocBook files and XML tools are also required.
Access to the DocBook 5.0 stylesheets and schema is required. The stylesheets are usually packaged by vendor, in something like docbook5-style-xsl. To exactly match generated output, please use a version of the stylesheets equivalent to
docbook5-style-xsl-1.75.2-3. The installation directory for this package corresponds to the XSL_STYLE_DIR in
doc/Makefile.am and defaults to /usr/share/sgml/docbook/xsl-ns-stylesheets.
For processing XML, an XSLT processor and some style sheets are necessary. Defaults are xsltproc provided by libxslt.
For validating the XML document, you’ll need something like xmllint and access to the relevant DocBook schema. These are
provided by a vendor package like libxml2 and docbook5-schemas-5.0-4
For PDF output, something that transforms valid Docbook XML to PDF is required. Possible solutions include dblatex, xmlto,
or prince. Of these, dblatex is the default. Please consult the libstdc++@gcc.gnu.org list when preparing printed manuals for
current best practice and suggestions.
For Texinfo output, something that transforms valid Docbook XML to Texinfo is required. The default choice is docbook2X.
For epub output, the stylesheets for EPUB3 are required. These stylesheets are still in development. To validate the created file,
epubcheck is necessary.
B.2.4.2

Generating the DocBook Files

The following Makefile rules generate (in order): an HTML version of all the DocBook documentation, a PDF version of the
same, and a single XML document. These rules are not conditional! If the required tools are not found, or are the wrong versions,
the rule may end in an error.

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make doc-html-docbook
make doc-pdf-docbook
make doc-xml-single-docbook

Generated files are output into separate sub directores of doc/docbook/ in the build directory, based on the output format.
For instance, the HTML docs will be in doc/docbook/html.
If the Docbook stylesheets are installed in a custom location, one can use the variable XSL_STYLE_DIR to override the Makefile
defaults. For example:
make XSL_STYLE_DIR="/usr/share/xml/docbook/stylesheet/nwalsh" doc-html-docbook

B.2.4.3

Debugging Generation

Sometimes, mis-configuration of the pre-requisite tools can lead to errors when attempting to build the documentation. Here are
some of the obvious errors, and ways to fix some common issues that may appear quite cryptic.
First, if using a rule like make pdf, try to narrow down the scope of the error to either docbook (make doc-pdf-docbook)
or doxygen (make doc-pdf-doxygen).
Working on the docbook path only, closely examine the contents of the following build directory: build/target/libstdc+
+-v3/doc/docbook/latex. Pay attention to three files enclosed within, annotated as follows.
• spine.tex
The actual latex file, or partial latex file. This is generated via dblatex, and is the LaTeX version of the DocBook XML file
spine.xml. Go to a specific line, and look at the generated LaTeX, and try to deduce what markup in spine.xml is
causing it.
• spine.out
A log of the conversion from the XML form to the LaTeX form. This is a linear list, from the beginning of the spine.xml
file: the last entry of this file should be the end of the DocBook file. If it is truncated, then you know that the last entry is the
last part of the XML source file that is valid. The error is after this point.
• spine.log
A log of the compilation of the converted LaTeX form to pdf. This is a linear list, from the beginning of the spine.tex file:
the last entry of this file should be the end of the LaTeX file. If it is truncated, then you know that the last entry is the last part
of the generated LaTeX source file that is valid. Often this file contains an error with a specific line number of spine.tex
that is incorrect.
If the error at hand is not obvious after examination, or if one encounters the inscruitable “Incomplete \ifmmode” error, a fall-back
strategy is to start commenting out parts of the XML document (regardless of what this does to over-all document validity). Start
by commenting out each of the largest parts of the spine.xml file, section by section, until the offending section is identified.
B.2.4.4

Editing and Validation

After editing the xml sources, please make sure that the XML documentation and markup is still valid. This can be done easily,
with the following validation rule:
make doc-xml-validate-docbook

This is equivalent to doing:

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xmllint --noout --valid xml/index.xml

Please note that individual sections and chapters of the manual can be validated by substituting the file desired for xml/index.
xml in the command above. Reducing scope in this manner can be helpful when validation on the entire manual fails.
All Docbook xml sources should always validate. No excuses!
B.2.4.5

File Organization and Basics

Which files are important
All Docbook files are in the directory
libstdc++-v3/doc/xml
Inside this directory, the files of importance:
spine.xml
- index to documentation set
manual/spine.xml - index to manual
manual/*.xml
- individual chapters and sections of the manual
faq.xml
- index to FAQ
api.xml
- index to source level / API
All *.txml files are template xml files, i.e., otherwise empty files with
the correct structure, suitable for filling in with new information.
Canonical Writing Style
class template
function template
member function template
(via C++ Templates, Vandevoorde)
class in namespace std: allocator, not std::allocator
header file: iostream, not 

General structure














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B.2.4.6

Markup By Example

Complete details on Docbook markup can be found in the DocBook Element Reference. An incomplete reference for HTML to
Docbook conversion is detailed in the table below.
HTML











"

Docbook

, , 







, 



Table B.4: HTML to Docbook XML Markup Comparison

And examples of detailed markup for which there are no real HTML equivalents are listed in the table below.

B.3

Porting to New Hardware or Operating Systems

This document explains how to port libstdc++ (the GNU C++ library) to a new target.
In order to make the GNU C++ library (libstdc++) work with a new target, you must edit some configuration files and provide
some new header files. Unless this is done, libstdc++ will use generic settings which may not be correct for your target; even if
they are correct, they will likely be inefficient.
Before you get started, make sure that you have a working C library on your target. The C library need not precisely comply with
any particular standard, but should generally conform to the requirements imposed by the ANSI/ISO standard.
In addition, you should try to verify that the C++ compiler generally works. It is difficult to test the C++ compiler without a
working library, but you should at least try some minimal test cases.
(Note that what we think of as a "target," the library refers to as a "host." The comment at the top of configure.ac explains
why.)

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Element











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Use
char_traits
string
clear()
fs.clear()
long long
fs
-Weffc++
rel_ops
_GNU_SOURCE
3.0
g++
In instantiation of
ctype.h
/home/gcc/build
libstdc++.so
Table B.5: Docbook XML Element Use

B.3.1

Operating System

If you are porting to a new operating system (as opposed to a new chip using an existing operating system), you will need to
create a new directory in the config/os hierarchy. For example, the IRIX configuration files are all in config/os/irix.
There is no set way to organize the OS configuration directory. For example, config/os/solaris/solaris-2.6 and
config/os/solaris/solaris-2.7 are used as configuration directories for these two versions of Solaris. On the other
hand, both Solaris 2.7 and Solaris 2.8 use the config/os/solaris/solaris-2.7 directory. The important information
is that there needs to be a directory under config/os to store the files for your operating system.
You might have to change the configure.host file to ensure that your new directory is activated. Look for the switch
statement that sets os_include_dir, and add a pattern to handle your operating system if the default will not suffice. The
switch statement switches on only the OS portion of the standard target triplet; e.g., the solaris2.8 in sparc-sun-solar
is2.8. If the new directory is named after the OS portion of the triplet (the default), then nothing needs to be changed.
The first file to create in this directory, should be called os_defines.h. This file contains basic macro definitions that are
required to allow the C++ library to work with your C library.
Several libstdc++ source files unconditionally define the macro _POSIX_SOURCE. On many systems, defining this macro
causes large portions of the C library header files to be eliminated at preprocessing time. Therefore, you may have to #undef
this macro, or define other macros (like _LARGEFILE_SOURCE or __EXTENSIONS__). You won’t know what macros to
define or undefine at this point; you’ll have to try compiling the library and seeing what goes wrong. If you see errors about
calling functions that have not been declared, look in your C library headers to see if the functions are declared there, and then
figure out what macros you need to define. You will need to add them to the CPLUSPLUS_CPP_SPEC macro in the GCC
configuration file for your target. It will not work to simply define these macros in os_defines.h.
At this time, there are a few libstdc++-specific macros which may be defined:
_GLIBCXX_USE_C99_CHECK may be defined to 1 to check C99 function declarations (which are not covered by specialization
below) found in system headers against versions found in the library headers derived from the standard.
_GLIBCXX_USE_C99_DYNAMIC may be defined to an expression that yields 0 if and only if the system headers are exposing
proper support for C99 functions (which are not covered by specialization below). If defined, it must be 0 while bootstrapping
the compiler/rebuilding the library.
_GLIBCXX_USE_C99_LONG_LONG_CHECK may be defined to 1 to check the set of C99 long long function declarations
found in system headers against versions found in the library headers derived from the standard.
_GLIBCXX_USE_C99_LONG_LONG_DYNAMIC may be defined to an expression that yields 0 if and only if the system headers
are exposing proper support for the set of C99 long long functions. If defined, it must be 0 while bootstrapping the compiler/rebuilding the library.

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_GLIBCXX_USE_C99_FP_MACROS_DYNAMIC may be defined to an expression that yields 0 if and only if the system headers
are exposing proper support for the related set of macros. If defined, it must be 0 while bootstrapping the compiler/rebuilding the
library.
_GLIBCXX_USE_C99_FLOAT_TRANSCENDENTALS_CHECK may be defined to 1 to check the related set of function declarations found in system headers against versions found in the library headers derived from the standard.
_GLIBCXX_USE_C99_FLOAT_TRANSCENDENTALS_DYNAMIC may be defined to an expression that yields 0 if and only if
the system headers are exposing proper support for the related set of functions. If defined, it must be 0 while bootstrapping the
compiler/rebuilding the library.
_GLIBCXX_NO_OBSOLETE_ISINF_ISNAN_DYNAMIC may be defined to an expression that yields 0 if and only if the
system headers are exposing non-standard isinf(double) and isnan(double) functions in the global namespace. Those
functions should be detected automatically by the configure script when libstdc++ is built but if their presence depends on
compilation flags or other macros the static configuration can be overridden.
Finally, you should bracket the entire file in an include-guard, like this:
#ifndef _GLIBCXX_OS_DEFINES
#define _GLIBCXX_OS_DEFINES
...
#endif

We recommend copying an existing os_defines.h to use as a starting point.

B.3.2

CPU

If you are porting to a new chip (as opposed to a new operating system running on an existing chip), you will need to create a new
directory in the config/cpu hierarchy. Much like the Operating system setup, there are no strict rules on how to organize the
CPU configuration directory, but careful naming choices will allow the configury to find your setup files without explicit help.
We recommend that for a target triplet --, you name your configuration directory config/cpu/
. If you do this, the configury will find the directory by itself. Otherwise you will need to edit the configure.host
file and, in the switch statement that sets cpu_include_dir, add a pattern to handle your chip.
Note that some chip families share a single configuration directory, for example, alpha, alphaev5, and alphaev6 all use
the config/cpu/alpha directory, and there is an entry in the configure.host switch statement to handle this.
The cpu_include_dir sets default locations for the files controlling Thread safety and Numeric limits, if the defaults are not
appropriate for your chip.

B.3.3

Character Types

The library requires that you provide three header files to implement character classification, analogous to that provided by the C
libraries  header. You can model these on the files provided in config/os/generic. However, these files will
almost certainly need some modification.
The first file to write is ctype_base.h. This file provides some very basic information about character classification. The
libstdc++ library assumes that your C library implements  by using a table (indexed by character code) containing
integers, where each of these integers is a bit-mask indicating whether the character is upper-case, lower-case, alphabetic, etc.
The ctype_base.h file gives the type of the integer, and the values of the various bit masks. You will have to peer at your
own  to figure out how to define the values required by this file.
The ctype_base.h header file does not need include guards. It should contain a single struct definition called ctype_
base. This struct should contain two type declarations, and one enumeration declaration, like this example, taken from the
IRIX configuration:
struct ctype_base
{
typedef unsigned int

mask;

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__to_type;

enum
{
space = _ISspace,
print = _ISprint,
cntrl = _IScntrl,
upper = _ISupper,
lower = _ISlower,
alpha = _ISalpha,
digit = _ISdigit,
punct = _ISpunct,
xdigit = _ISxdigit,
alnum = _ISalnum,
graph = _ISgraph
};
};

The mask type is the type of the elements in the table. If your C library uses a table to map lower-case numbers to upper-case
numbers, and vice versa, you should define __to_type to be the type of the elements in that table. If you don’t mind taking
a minor performance penalty, or if your library doesn’t implement toupper and tolower in this way, you can pick any
pointer-to-integer type, but you must still define the type.
The enumeration should give definitions for all the values in the above example, using the values from your native .
They can be given symbolically (as above), or numerically, if you prefer. You do not have to include  in this header;
it will always be included before ctype_base.h is included.
The next file to write is ctype_configure_char.cc. The first function that must be written is the ctype::
ctype constructor. Here is the IRIX example:
ctype::ctype(const mask* __table = 0, bool __del = false,
size_t __refs = 0)
: _Ctype_nois(__refs), _M_del(__table != 0 && __del),
_M_toupper(NULL),
_M_tolower(NULL),
_M_ctable(NULL),
_M_table(!__table
? (const mask*) (__libc_attr._ctype_tbl->_class + 1)
: __table)
{ }

There are two parts of this that you might choose to alter. The first, and most important, is the line involving __libc_attr.
That is IRIX system-dependent code that gets the base of the table mapping character codes to attributes. You need to substitute
code that obtains the address of this table on your system. If you want to use your operating system’s tables to map upper-case
letters to lower-case, and vice versa, you should initialize _M_toupper and _M_tolower with those tables, in similar fashion.
Now, you have to write two functions to convert from upper-case to lower-case, and vice versa. Here are the IRIX versions:
char
ctype::do_toupper(char __c) const
{ return _toupper(__c); }
char
ctype::do_tolower(char __c) const
{ return _tolower(__c); }

Your C library provides equivalents to IRIX’s _toupper and _tolower. If you initialized _M_toupper and _M_tolower
above, then you could use those tables instead.
Finally, you have to provide two utility functions that convert strings of characters. The versions provided here will always work
- but you could use specialized routines for greater performance if you have machinery to do that on your system:

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const char*
ctype::do_toupper(char* __low, const char* __high) const
{
while (__low < __high)
{
*__low = do_toupper(*__low);
++__low;
}
return __high;
}
const char*
ctype::do_tolower(char* __low, const char* __high) const
{
while (__low < __high)
{
*__low = do_tolower(*__low);
++__low;
}
return __high;
}

You must also provide the ctype_inline.h file, which contains a few more functions. On most systems, you can just copy
config/os/generic/ctype_inline.h and use it on your system.
In detail, the functions provided test characters for particular properties; they are analogous to the functions like isalpha and
islower provided by the C library.
The first function is implemented like this on IRIX:
bool
ctype::
is(mask __m, char __c) const throw()
{ return (_M_table)[(unsigned char)(__c)] & __m; }

The _M_table is the table passed in above, in the constructor. This is the table that contains the bitmasks for each character.
The implementation here should work on all systems.
The next function is:
const char*
ctype::
is(const char* __low, const char* __high, mask* __vec) const throw()
{
while (__low < __high)
*__vec++ = (_M_table)[(unsigned char)(*__low++)];
return __high;
}

This function is similar; it copies the masks for all the characters from __low up until __high into the vector given by __vec.
The last two functions again are entirely generic:
const char*
ctype::
scan_is(mask __m, const char* __low, const char* __high) const throw()
{
while (__low < __high && !this->is(__m, *__low))
++__low;
return __low;
}

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const char*
ctype::
scan_not(mask __m, const char* __low, const char* __high) const throw()
{
while (__low < __high && this->is(__m, *__low))
++__low;
return __low;
}

B.3.4

Thread Safety

The C++ library string functionality requires a couple of atomic operations to provide thread-safety. If you don’t take any special
action, the library will use stub versions of these functions that are not thread-safe. They will work fine, unless your applications
are multi-threaded.
If you want to provide custom, safe, versions of these functions, there are two distinct approaches. One is to provide a version
for your CPU, using assembly language constructs. The other is to use the thread-safety primitives in your operating system. In
either case, you make a file called atomicity.h, and the variable ATOMICITYH must point to this file.
If you are using the assembly-language approach, put this code in config/cpu//atomicity.h, where chip is the
name of your processor (see CPU). No additional changes are necessary to locate the file in this case; ATOMICITYH will be set
by default.
If you are using the operating system thread-safety primitives approach, you can also put this code in the same CPU directory,
in which case no more work is needed to locate the file. For examples of this approach, see the atomicity.h file for IRIX or
IA64.
Alternatively, if the primitives are more closely related to the OS than they are to the CPU, you can put the atomicity.h
file in the Operating system directory instead. In this case, you must edit configure.host, and in the switch statement that
handles operating systems, override the ATOMICITYH variable to point to the appropriate os_include_dir. For examples
of this approach, see the atomicity.h file for AIX.
With those bits out of the way, you have to actually write atomicity.h itself. This file should be wrapped in an include guard
named _GLIBCXX_ATOMICITY_H. It should define one type, and two functions.
The type is _Atomic_word. Here is the version used on IRIX:
typedef long _Atomic_word;

This type must be a signed integral type supporting atomic operations. If you’re using the OS approach, use the same type used
by your system’s primitives. Otherwise, use the type for which your CPU provides atomic primitives.
Then, you must provide two functions. The bodies of these functions must be equivalent to those provided here, but using atomic
operations:
static inline _Atomic_word
__attribute__ ((__unused__))
__exchange_and_add (_Atomic_word* __mem, int __val)
{
_Atomic_word __result = *__mem;
*__mem += __val;
return __result;
}
static inline void
__attribute__ ((__unused__))
__atomic_add (_Atomic_word* __mem, int __val)
{
*__mem += __val;
}

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Numeric Limits

The C++ library requires information about the fundamental data types, such as the minimum and maximum representable values
of each type. You can define each of these values individually, but it is usually easiest just to indicate how many bits are used
in each of the data types and let the library do the rest. For information about the macros to define, see the top of include/
bits/std_limits.h.
If you need to define any macros, you can do so in os_defines.h. However, if all operating systems for your CPU are likely
to use the same values, you can provide a CPU-specific file instead so that you do not have to provide the same definitions for
each operating system. To take that approach, create a new file called cpu_limits.h in your CPU configuration directory
(see CPU).

B.3.6

Libtool

The C++ library is compiled, archived and linked with libtool. Explaining the full workings of libtool is beyond the scope of this
document, but there are a few, particular bits that are necessary for porting.
Some parts of the libstdc++ library are compiled with the libtool --tags CXX option (the C++ definitions for libtool). Therefore, ltcf-cxx.sh in the top-level directory needs to have the correct logic to compile and archive objects equivalent to the C
version of libtool, ltcf-c.sh. Some libtool targets have definitions for C but not for C++, or C++ definitions which have not
been kept up to date.
The C++ run-time library contains initialization code that needs to be run as the library is loaded. Often, that requires linking in
special object files when the C++ library is built as a shared library, or taking other system-specific actions.
The libstdc++ library is linked with the C version of libtool, even though it is a C++ library. Therefore, the C version of libtool
needs to ensure that the run-time library initializers are run. The usual way to do this is to build the library using gcc -shared.
If you need to change how the library is linked, look at ltcf-c.sh in the top-level directory. Find the switch statement that
sets archive_cmds. Here, adjust the setting for your operating system.

B.4

Testing

The libstdc++ testsuite includes testing for standard conformance, regressions, ABI, and performance.

B.4.1

Test Organization

B.4.1.1

Directory Layout

The directory gccsrcdir /libstdc++-v3/testsuite contains the individual test cases organized in sub-directories corresponding to clauses of the C++ standard (detailed below), the DejaGnu test harness support files, and sources to various testsuite
utilities that are packaged in a separate testing library.
All test cases for functionality required by the runtime components of the C++ standard (ISO 14882) are files within the following
directories:
17_intro
18_support
19_diagnostics
20_util
21_strings
22_locale
23_containers
24_iterators
25_algorithms
26_numerics
27_io
28_regex

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29_atomics
30_threads

In addition, the following directories include test files:
tr1 Tests for components as described by the Technical Report on Standard Library Extensions (TR1).
backward Tests for backwards compatibility and deprecated features.
demangle Tests for __cxa_demangle, the IA-64 C++ ABI demangler.
ext Tests for extensions.
performance Tests for performance analysis, and performance regressions.
Some directories don’t have test files, but instead contain auxiliary information:
config Files for the DejaGnu test harness.
lib Files for the DejaGnu test harness.
libstdc++* Files for the DejaGnu test harness.
data Sample text files for testing input and output.
util Files for libtestc++, utilities and testing routines.
Within a directory that includes test files, there may be additional subdirectories, or files. Originally, test cases were appended
to one file that represented a particular section of the chapter under test, and was named accordingly. For instance, to test items
related to 21.3.6.1 -basic_string::find [lib.string::find] in the standard, the following was used:
21_strings/find.cc

However, that practice soon became a liability as the test cases became huge and unwieldy, and testing new or extended functionality (like wide characters or named locales) became frustrating, leading to aggressive pruning of test cases on some platforms
that covered up implementation errors. Now, the test suite has a policy of one file, one test case, which solves the above issues
and gives finer grained results and more manageable error debugging. As an example, the test case quoted above becomes:
21_strings/basic_string/find/char/1.cc
21_strings/basic_string/find/char/2.cc
21_strings/basic_string/find/char/3.cc
21_strings/basic_string/find/wchar_t/1.cc
21_strings/basic_string/find/wchar_t/2.cc
21_strings/basic_string/find/wchar_t/3.cc

All new tests should be written with the policy of "one test case, one file" in mind.
B.4.1.2

Naming Conventions

In addition, there are some special names and suffixes that are used within the testsuite to designate particular kinds of tests.
_xin.cc This test case expects some kind of interactive input in order to finish or pass. At the moment, the interactive tests
are not run by default. Instead, they are run by hand, like:
g++ 27_io/objects/char/3_xin.cc
cat 27_io/objects/char/3_xin.in | a.out

.in This file contains the expected input for the corresponding _xin.cc test case.
_neg.cc This test case is expected to fail: it’s a negative test. At the moment, these are almost always compile time errors.

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char This can either be a directory name or part of a longer file name, and indicates that this file, or the files within this directory
are testing the char instantiation of a template.
wchar_t This can either be a directory name or part of a longer file name, and indicates that this file, or the files within this
directory are testing the wchar_t instantiation of a template. Some hosts do not support wchar_t functionality, so for
these targets, all of these tests will not be run.
thread This can either be a directory name or part of a longer file name, and indicates that this file, or the files within this
directory are testing situations where multiple threads are being used.
performance This can either be an enclosing directory name or part of a specific file name. This indicates a test that is
used to analyze runtime performance, for performance regression testing, or for other optimization related analysis. At the
moment, these test cases are not run by default.

B.4.2

Running the Testsuite

B.4.2.1

Basic

You can check the status of the build without installing it using the DejaGnu harness, much like the rest of the gcc tools, i.e.
make check in the libbuilddir directory, or make check-target-libstdc++-v3 in the gccbuilddir directory.
These commands are functionally equivalent and will create a ’testsuite’ directory underneath libbuilddir containing
the results of the tests. Two results files will be generated: libstdc++.sum, which is a PASS/FAIL summary for each test,
and libstdc++.log which is a log of the exact command-line passed to the compiler, the compiler output, and the executable
output (if any) for each test.
Archives of test results for various versions and platforms are available on the GCC website in the build status section of each
individual release, and are also archived on a daily basis on the gcc-testresults mailing list. Please check either of these places
for a similar combination of source version, operating system, and host CPU.
B.4.2.2

Variations

There are several options for running tests, including testing the regression tests, testing a subset of the regression tests, testing
the performance tests, testing just compilation, testing installed tools, etc. In addition, there is a special rule for checking the
exported symbols of the shared library.
To debug the DejaGnu test harness during runs, try invoking with a specific argument to the variable RUNTESTFLAGS, like so:
make check-target-libstdc++-v3 RUNTESTFLAGS="-v"

or
make check-target-libstdc++-v3 RUNTESTFLAGS="-v -v"

To run a subset of the library tests, you can either generate the testsuite_files file (described below) by running make
testsuite_files in the libbuilddir /testsuite directory, then edit the file to remove the tests you don’t want and
then run the testsuite as normal, or you can specify a testsuite and a subset of tests in the RUNTESTFLAGS variable.
For example, to run only the tests for containers you could use:
make check-target-libstdc++-v3 RUNTESTFLAGS="conformance.exp=23_containers/*"

When combining this with other options in RUNTESTFLAGS the testsuite.exp=testfiles options must come first.
There are two ways to run on a simulator: set up DEJAGNU to point to a specially crafted site.exp, or pass down -target_board flags.
Example flags to pass down for various embedded builds are as follows:

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--target=powerpc-eabisim (libgloss/sim)
make check-target-libstdc++-v3 RUNTESTFLAGS="--target_board=powerpc-sim"
--target=calmrisc32 (libgloss/sid)
make check-target-libstdc++-v3 RUNTESTFLAGS="--target_board=calmrisc32-sid"
--target=xscale-elf (newlib/sim)
make check-target-libstdc++-v3 RUNTESTFLAGS="--target_board=arm-sim"

Also, here is an example of how to run the libstdc++ testsuite for a multilibed build directory with different ABI settings:
make check-target-libstdc++-v3 RUNTESTFLAGS=’--target_board \"unix{-mabi=32,,-mabi ←=64}\"’

You can run the tests with a compiler and library that have already been installed. Make sure that the compiler (e.g., g++) is
in your PATH. If you are using shared libraries, then you must also ensure that the directory containing the shared version of
libstdc++ is in your LD_LIBRARY_PATH, or equivalent. If your GCC source tree is at /path/to/gcc, then you can run the
tests as follows:
runtest --tool libstdc++ --srcdir=/path/to/gcc/libstdc++-v3/testsuite

The testsuite will create a number of files in the directory in which you run this command,. Some of those files might use the
same name as files created by other testsuites (like the ones for GCC and G++), so you should not try to run all the testsuites in
parallel from the same directory.
In addition, there are some testing options that are mostly of interest to library maintainers and system integrators. As such,
these tests may not work on all CPU and host combinations, and may need to be executed in the libbuilddir /testsuite
directory. These options include, but are not necessarily limited to, the following:
make testsuite_files

Five files are generated that determine what test files are run. These files are:

testsuite_files This is a list of all the test cases that will be run. Each test case is on a separate line, given with
an absolute path from the libsrcdir /testsuite directory.
testsuite_files_interactive This is a list of all the interactive test cases, using the same format as the file
list above. These tests are not run by default.
testsuite_files_performance This is a list of all the performance test cases, using the same format as the file
list above. These tests are not run by default.
testsuite_thread This file indicates that the host system can run tests which involved multiple threads.
testsuite_wchar_t This file indicates that the host system can run the wchar_t tests, and corresponds to the
macro definition _GLIBCXX_USE_WCHAR_T in the file c++config.h.
make check-abi The library ABI can be tested. This involves testing the shared library against a baseline list of symbol
exports that defines the previous version of the ABI. The tests require that no exported symbols are removed, no new
symbols are added to the old symbol versions, and any new symbols have the latest symbol version. See Versioning for
more details of the ABI version history.
make new-abi-baseline Generate a new baseline set of symbols exported from the library (written to a file under
libsrcdir /config/abi/post/target/). A different baseline symbols file is needed for each architecture and is
used by the check-abi target described above. The files are usually re-generated by target maintainers for releases.
make check-compile
the output on stdout.

This rule compiles, but does not link or execute, the testsuite_files test cases and displays

make check-performance This rule runs through the testsuite_files_performance test cases and collects
information for performance analysis and can be used to spot performance regressions. Various timing information is
collected, as well as number of hard page faults, and memory used. This is not run by default, and the implementation is
in flux.
make check-debug

This rule runs through the test suite under the debug mode.

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This rule runs through the test suite under the parallel mode.

We are interested in any strange failures of the testsuite; please email the main libstdc++ mailing list if you see something odd or
have questions.
B.4.2.3

Permutations

The tests will be compiled with a set of default compiler flags defined by the libbuilddir /scripts/testsuite_flags
file, as well as options specified in individual tests. You can run the tests with different options by adding them to the output
of the --cxxflags option of that script, or by setting the CXXFLAGS variable when running make, or via options for the
DejaGnu test framework (described below). The latter approach uses the --target_board option that was shown earlier, but
requires DejaGnu version 1.5.3 or newer to work reliably, so that the dg-options in the test aren’t overridden. For example,
to run the tests with -O1 -D_GLIBCXX_ASSERTIONS you could use:
make check RUNTESTFLAGS=--target_board=unix/-O1/-D_GLIBCXX_ASSERTIONS

The --target_board option can also be used to run the tests multiple times in different variations. For example, to run the
entire testsuite three times using -O3 but with different -std options:
make check ’RUNTESTFLAGS=--target_board=unix/-O3\"{-std=gnu++98,-std=gnu++11,-std=gnu ←++14}\"’

N.B. that set of variations could also be written as unix/-O3\"{-std=gnu++98,-std=gnu++11,}\" so that the third
variation would use the default for -std (which is -std=gnu++14 as of GCC 6).
To run the libstdc++ test suite under the debug mode, use make check-debug. Alternatively, edit libbuilddir /scripts/
testsuite_flags to add the compile-time flag -D_GLIBCXX_DEBUG to the result printed by the --cxxflags option.
Additionally, add the -D_GLIBCXX_DEBUG_PEDANTIC flag to turn on pedantic checking. The libstdc++ test suite should
produce the same results under debug mode that it does under release mode: any deviation indicates an error in either the library
or the test suite. Note, however, that the number of tests that PASS may change, because some test cases are skipped in normal
mode, and some are skipped in debug mode, as determined by the dg-require-support directives described below.
The parallel mode can be tested using make check-parallel, or in much the same manner as the debug mode, substituting
-D_GLIBCXX_PARALLEL for -D_GLIBCXX_DEBUG in the previous paragraph.
Or, just run the testsuite -D_GLIBCXX_DEBUG or -D_GLIBCXX_PARALLEL in CXXFLAGS or RUNTESTFLAGS.

B.4.3

Writing a new test case

The first step in making a new test case is to choose the correct directory and file name, given the organization as previously
described.
All files are copyright the FSF, and GPL’d: this is very important. The first copyright year should correspond to the date the file
was checked in to version control. If a test is copied from an existing file it should retain the copyright years from the original
file.
The DejaGnu instructions say to always return 0 from main to indicate success. Strictly speaking this is redundant in C++, since
returning from main is defined to return 0. Most tests still have an explicit return.
A bunch of utility functions and classes have already been abstracted out into the testsuite utility library, libtestc++. To
use this functionality, just include the appropriate header file: the library or specific object files will automatically be linked in as
part of the testsuite run.
Tests that need to perform runtime checks should use the VERIFY macro, defined in the  header.
This usually expands to the standard assert macro, but allows targets to define it to something different. In order to support the
alternative expansions of VERIFY, before any use of the macro there must be a variable called test in scope, which is usually
defined like so (the attribute avoids warnings about an unused variable):
bool test __attribute__((unused)) = true;

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The testsuite uses the DejaGnu framework to compile and run the tests. Test cases are normal C++ files which contain special
directives in comments. These directives look like { dg-* ...} and tell DejaGnu what to do and what kinds of behavior
are to be expected for a test. The core DejaGnu directives are documented in the dg.exp file installed by DejaGnu. The GCC
testsuites support additional directives as described in the GCC internals documentation, see Syntax and Descriptions of test
directives. GCC also defines many Keywords describing target attributes (a.k.a effective targets) which can be used where a
target selector can appear.
Some directives commonly used in the libstdc++ testsuite are:
{ dg-do do-what-keyword [{ target/xfail selector }] } Where do-what-keyword is usually one of run
(which is the default), compile, or link, and typical selectors are targets such as *-*-gnu* or an effective target such
as c++11.
{ dg-require-support args } Skip the test if the target does not provide the required support. See below for values of
support.
{ dg-options options [{ target selector }] }
{ dg-error regexp [ comment [{ target/xfail selector } [line] ]] }
{ dg-excess-errors comment [{ target/xfail selector }] }
For full details of these and other directives see the main GCC DejaGnu documentation in the internals manual.
Test cases that use features of a particular C++ standard should specify the minimum required standard as an effective target:
// { dg-do run { target c++11 } }

or
// { dg-require-effective-target c++11 }

Specifying the minimum required standard for a test allows it to be run using later standards, so that we can verify that C++11
components still work correctly when compiled as C++14 or later. Specifying a minimum also means the test will be skipped if
the test is compiled using an older standard, e.g. using RUNTESTFLAGS=--target_board=unix/-std=gnu++98.
It is possible to indicate that a test should only be run for a specific standard (and not later standards) using an effective target
like c++11_only. However, this means the test will be skipped by default (because the default mode is gnu++14), and so will
only run when -std=gnu++11 or -std=c++11 is used explicitly. For tests that require a specific standard it is better to use
a dg-options directive:
// { dg-options "-std=gnu++11" }

This means the test will not get skipped by default, and will always use the specific standard dialect that the test requires. This
isn’t needed often, and most tests should use an effective target to specify a minimum standard instead, to allow them to be tested
for all possible variations.
Similarly, tests which depend on a newer standard than the default should use dg-options instead of an effective target, so
that they are not skipped by default. For example, tests for C++17 features should use
// { dg-options "-std=gnu++17" }

and not
// { dg-do run "c++1z" }

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Examples of Test Directives

Example 1: Testing compilation only:
// { dg-do compile }

Example 2: Testing for expected warnings on line 36, which all targets fail:
// { dg-warning "string literals" "" { xfail *-*-* } 36 }

Example 3: Testing for expected warnings on line 36:
// { dg-warning "string literals" "" { target *-*-* } 36 }

Example 4: Testing for compilation errors on line 41:
// { dg-do compile }
// { dg-error "no match for" "" { target *-*-* } 41 }

Example 5: Testing with special command line settings, or without the use of pre-compiled headers, in particular the stdc++.
h.gch file. Any options here will override the DEFAULT_CXXFLAGS and PCH_CXXFLAGS set up in the normal.exp file:
// { dg-options "-O0" { target *-*-* } }

Example 6: Compiling and linking a test only for C++14 and later, and only if Debug Mode is active:
// { dg-do link { target c++14 } }
// { dg-require-debug-mode "" }

Example 7: Running a test only on x86 targets, and only for C++11 and later, with specific options, and additional options for
32-bit x86:
//
//
//
//

{
{
{
{

dg-options "-fstrict-enums" }
dg-additional-options "-march=i486" { target ia32 } }
dg-do run { target { ia32 || x86_64-*-* } } }
dg-require-effective-target "c++11" }

More examples can be found in the libstdc++-v3/testsuite/*/*.cc files.
B.4.3.2

Directives Specific to Libstdc++ Tests

In addition to the usual Variants of dg-require-support several more directives are available for use in libstdc++ tests,
including the following:
dg-require-namedlocale name The named locale must be available.
dg-require-debug-mode "" Skip the test if the Debug Mode is not active (as determined by the _GLIBCXX_DEBUG
macro).
dg-require-parallel-mode "" Skip the test if the Parallel Mode is not active (as determined by the _GLIBCXX_PAR
ALLEL macro).
dg-require-profile-mode "" Skip the test if the Profile Mode is not active (as determined by the _GLIBCXX_PROF
ILE macro).
dg-require-normal-mode "" Skip the test if any of Debug, Parallel or Profile Mode is active.
dg-require-atomic-builtins "" Skip the test if atomic operations on bool and int are not lock-free.
dg-require-gthreads "" Skip the test if the C++11 thread library is not supported, as determined by the _GLIBCXX_H
AS_GTHREADS macro.

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dg-require-gthreads-timed "" Skip the test if C++11 timed mutexes are not supported, as determined by the _GLI
BCXX_HAS_GTHREADS and _GTHREAD_USE_MUTEX_TIMEDLOCK macros.
dg-require-string-conversions "" Skip the test if the C++11 to_string and stoi, stod etc. functions are
not fully supported (including wide character versions).
dg-require-filesystem-ts "" Skip the test if the Filesystem TS is not supported.

B.4.4

Test Harness and Utilities

B.4.4.1

DejaGnu Harness Details

Underlying details of testing for conformance and regressions are abstracted via the GNU DejaGnu package. This is similar to
the rest of GCC.
This is information for those looking at making changes to the testsuite structure, and/or needing to trace DejaGnu’s actions with
--verbose. This will not be useful to people who are "merely" adding new tests to the existing structure.
The first key point when working with DejaGnu is the idea of a "tool". Files, directories, and functions are all implicitly used
when they are named after the tool in use. Here, the tool will always be "libstdc++".
The lib subdir contains support routines. The lib/libstdc++.exp file ("support library") is loaded automagically, and
must explicitly load the others. For example, files can be copied from the core compiler’s support directory into lib.
Some routines in lib/libstdc++.exp are callbacks, some are our own. Callbacks must be prefixed with the name of the
tool. To easily distinguish the others, by convention our own routines are named "v3-*".
The next key point when working with DejaGnu is "test files". Any directory whose name starts with the tool name will be
searched for test files. (We have only one.) In those directories, any .exp file is considered a test file, and will be run in turn.
Our main test file is called normal.exp; it runs all the tests in testsuite_files using the callbacks loaded from the support library.
The config directory is searched for any particular "target board" information unique to this library. This is currently unused
and sets only default variables.
B.4.4.2

Utilities

The testsuite directory also contains some files that implement functionality that is intended to make writing test cases easier, or
to avoid duplication, or to provide error checking in a way that is consistent across platforms and test harnesses. A stand-alone
executable, called abi_check, and a static library called libtestc++ are constructed. Both of these items are not installed, and only
used during testing.
These files include the following functionality:
• testsuite_abi.h, testsuite_abi.cc, testsuite_abi_check.cc
Creates the executable abi_check. Used to check correctness of symbol versioning, visibility of exported symbols, and compatibility on symbols in the shared library, for hosts that support this feature. More information can be found in the ABI
documentation here
• testsuite_allocator.h, testsuite_allocator.cc
Contains specialized allocators that keep track of construction and destruction. Also, support for overriding global new and
delete operators, including verification that new and delete are called during execution, and that allocation over max_size fails.
• testsuite_character.h
Contains std::char_traits and std::codecvt specializations for a user-defined POD.
• testsuite_hooks.h, testsuite_hooks.cc
A large number of utilities, including:
– VERIFY

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– set_memory_limits
– verify_demangle
– run_tests_wrapped_locale
– run_tests_wrapped_env
– try_named_locale
– try_mkfifo
– func_callback
– counter
– copy_tracker
– copy_constructor
– assignment_operator
– destructor
– pod_char, pod_int and associated char_traits specializations
• testsuite_io.h
Error, exception, and constraint checking for std::streambuf, std::basic_stringbuf, std::basic_file
buf.
• testsuite_iterators.h
Wrappers for various iterators.
• testsuite_performance.h
A number of class abstractions for performance counters, and reporting functions including:
– time_counter
– resource_counter
– report_performance

B.4.5
B.4.5.1
B.4.5.1.1

Special Topics
Qualifying Exception Safety Guarantees
Overview

Testing is composed of running a particular test sequence, and looking at what happens to the surrounding code when exceptions
are thrown. Each test is composed of measuring initial state, executing a particular sequence of code under some instrumented
conditions, measuring a final state, and then examining the differences between the two states.
Test sequences are composed of constructed code sequences that exercise a particular function or member function, and either
confirm no exceptions were generated, or confirm the consistency/coherency of the test subject in the event of a thrown exception.
Random code paths can be constructed using the basic test sequences and instrumentation as above, only combined in a random
or pseudo-random way.
To compute the code paths that throw, test instruments are used that throw on allocation events (__gnu_cxx::throw_alloc
ator_random and __gnu_cxx::throw_allocator_limit) and copy, assignment, comparison, increment, swap, and
various operators (__gnu_cxx::throw_type_random and __gnu_cxx::throw_type_limit). Looping through a
given test sequence and conditionally throwing in all instrumented places. Then, when the test sequence completes without an
exception being thrown, assume all potential error paths have been exercised in a sequential manner.

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Existing tests

• Ad Hoc
For example, testsuite/23_containers/list/modifiers/3.cc.
• Policy Based Data Structures
For example, take the test functor rand_reg_test in in testsuite/ext/pb_ds/regression/tree_no_data_
map_rand.cc. This uses container_rand_regression_test in testsuite/util/regression/rand/assoc/
container_rand_regression_test.h.
Which has several tests for container member functions, Includes control and test container objects. Configuration includes
random seed, iterations, number of distinct values, and the probability that an exception will be thrown. Assumes instantiating
container uses an extension allocator, __gnu_cxx::throw_allocator_random, as the allocator type.
• C++11 Container Requirements.
Coverage is currently limited to testing container requirements for exception safety, although __gnu_cxx::throw_type
meets the additional type requirements for testing numeric data structures and instantiating algorithms.
Of particular interest is extending testing to algorithms and then to parallel algorithms. Also io and locales.
The test instrumentation should also be extended to add instrumentation to iterator and const_iterator types that
throw conditionally on iterator operations.
B.4.5.1.3

C++11 Requirements Test Sequence Descriptions

• Basic
Basic consistency on exception propagation tests. For each container, an object of that container is constructed, a specific
member function is exercised in a try block, and then any thrown exceptions lead to error checking in the appropriate catch
block. The container’s use of resources is compared to the container’s use prior to the test block. Resource monitoring is
limited to allocations made through the container’s allocator_type, which should be sufficient for container data structures.
Included in these tests are member functions are iterator and const_iterator operations, pop_front, pop_back, push
_front, push_back, insert, erase, swap, clear, and rehash. The container in question is instantiated with
two instrumented template arguments, with __gnu_cxx::throw_allocator_limit as the allocator type, and with
__gnu_cxx::throw_type_limit as the value type. This allows the test to loop through conditional throw points.
The general form is demonstrated in testsuite/23_containers/list/requirements/exception/basic.
cc . The instantiating test object is __gnu_test::basic_safety and is detailed in testsuite/util/exception/
safety.h.
• Generation Prohibited
Exception generation tests. For each container, an object of that container is constructed and all member functions required
to not throw exceptions are exercised. Included in these tests are member functions are iterator and const_iterator operations,
erase, pop_front, pop_back, swap, and clear. The container in question is instantiated with two instrumented
template arguments, with __gnu_cxx::throw_allocator_random as the allocator type, and with __gnu_cxx::
throw_type_random as the value type. This test does not loop, an instead is sudden death: first error fails.

The general form is demonstrated in testsuite/23_containers/list/requirements/exception/generation_
prohibited.cc . The instantiating test object is __gnu_test::generation_prohibited and is detailed in testsuite/
util/exception/safety.h.
• Propagation Consistent
Container rollback on exception propagation tests. For each container, an object of that container is constructed, a specific
member function that requires rollback to a previous known good state is exercised in a try block, and then any thrown
exceptions lead to error checking in the appropriate catch block. The container is compared to the container’s last known
good state using such parameters as size, contents, and iterator references. Included in these tests are member functions
are push_front, push_back, insert, and rehash. The container in question is instantiated with two instrumented
template arguments, with __gnu_cxx::throw_allocator_limit as the allocator type, and with __gnu_cxx::thr
ow_type_limit as the value type. This allows the test to loop through conditional throw points.
The general form demonstrated in testsuite/23_containers/list/requirements/exception/propagation_
coherent.cc . The instantiating test object is __gnu_test::propagation_coherent and is detailed in testsuite/
util/exception/safety.h.

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ABI Policy and Guidelines
The C++ Interface

C++ applications often depend on specific language support routines, say for throwing exceptions, or catching exceptions, and
perhaps also depend on features in the C++ Standard Library.
The C++ Standard Library has many include files, types defined in those include files, specific named functions, and other
behavior. The text of these behaviors, as written in source include files, is called the Application Programing Interface, or API.
Furthermore, C++ source that is compiled into object files is transformed by the compiler: it arranges objects with specific
alignment and in a particular layout, mangling names according to a well-defined algorithm, has specific arrangements for the
support of virtual functions, etc. These details are defined as the compiler Application Binary Interface, or ABI. From GCC
version 3 onwards the GNU C++ compiler uses an industry-standard C++ ABI, the Itanium C++ ABI.
The GNU C++ compiler, g++, has a compiler command line option to switch between various different C++ ABIs. This explicit
version switch is the flag -fabi-version. In addition, some g++ command line options may change the ABI as a side-effect
of use. Such flags include -fpack-struct and -fno-exceptions, but include others: see the complete list in the GCC
manual under the heading Options for Code Generation Conventions.
The configure options used when building a specific libstdc++ version may also impact the resulting library ABI. The available
configure options, and their impact on the library ABI, are documented here.
Putting all of these ideas together results in the C++ Standard Library ABI, which is the compilation of a given library API by a
given compiler ABI. In a nutshell:
“ library API + compiler ABI = library ABI ”
The library ABI is mostly of interest for end-users who have unresolved symbols and are linking dynamically to the C++
Standard library, and who thus must be careful to compile their application with a compiler that is compatible with the available
C++ Standard library binary. In this case, compatible is defined with the equation above: given an application compiled with a
given compiler ABI and library API, it will work correctly with a Standard C++ Library created with the same constraints.
To use a specific version of the C++ ABI, one must use a corresponding GNU C++ toolchain (i.e., g++ and libstdc++) that
implements the C++ ABI in question.

B.5.2

Versioning

The C++ interface has evolved throughout the history of the GNU C++ toolchain. With each release, various details have been
changed so as to give distinct versions to the C++ interface.
B.5.2.1

Goals

Extending existing, stable ABIs. Versioning gives subsequent releases of library binaries the ability to add new symbols and add
functionality, all the while retaining compatibility with the previous releases in the series. Thus, program binaries linked with the
initial release of a library binary will still run correctly if the library binary is replaced by carefully-managed subsequent library
binaries. This is called forward compatibility.
The reverse (backwards compatibility) is not true. It is not possible to take program binaries linked with the latest version of a
library binary in a release series (with additional symbols added), substitute in the initial release of the library binary, and remain
link compatible.
Allows multiple, incompatible ABIs to coexist at the same time.
B.5.2.2

History

How can this complexity be managed? What does C++ versioning mean? Because library and compiler changes often make
binaries compiled with one version of the GNU tools incompatible with binaries compiled with other (either newer or older)
versions of the same GNU tools, specific techniques are used to make managing this complexity easier.
The following techniques are used:

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1. Release versioning on the libgcc_s.so binary.
This is implemented via file names and the ELF DT_SONAME mechanism (at least on ELF systems). It is versioned as
follows:
• GCC 3.x: libgcc_s.so.1
• GCC 4.x: libgcc_s.so.1
For m68k-linux the versions differ as follows:
• GCC 3.4, GCC 4.x: libgcc_s.so.1 when configuring --with-sjlj-exceptions, or libgcc_s.so.2
For hppa-linux the versions differ as follows:
• GCC 3.4, GCC 4.[0-1]: either libgcc_s.so.1 when configuring --with-sjlj-exceptions, or libgcc_s.so.2
• GCC 4.[2-7]: either libgcc_s.so.3 when configuring --with-sjlj-exceptions) or libgcc_s.so.4
2. Symbol versioning on the libgcc_s.so binary.
It is versioned with the following labels and version definitions, where the version definition is the maximum for a particular
release. Labels are cumulative. If a particular release is not listed, it has the same version labels as the preceding release.
This corresponds to the mapfile: gcc/libgcc-std.ver
• GCC 3.0.0: GCC_3.0
• GCC 3.3.0: GCC_3.3
• GCC 3.3.1: GCC_3.3.1
• GCC 3.3.2: GCC_3.3.2
• GCC 3.3.4: GCC_3.3.4
• GCC 3.4.0: GCC_3.4
• GCC 3.4.2: GCC_3.4.2
• GCC 3.4.4: GCC_3.4.4
• GCC 4.0.0: GCC_4.0.0
• GCC 4.1.0: GCC_4.1.0
• GCC 4.2.0: GCC_4.2.0
• GCC 4.3.0: GCC_4.3.0
• GCC 4.4.0: GCC_4.4.0
• GCC 4.5.0: GCC_4.5.0
• GCC 4.6.0: GCC_4.6.0
• GCC 4.7.0: GCC_4.7.0
• GCC 4.8.0: GCC_4.8.0
3. Release versioning on the libstdc++.so binary, implemented in the same way as the libgcc_s.so binary above. Listed
is the filename: DT_SONAME can be deduced from the filename by removing the last two period-delimited numbers.
For example, filename libstdc++.so.5.0.4 corresponds to a DT_SONAME of libstdc++.so.5. Binaries with
equivalent DT_SONAMEs are forward-compatibile: in the table below, releases incompatible with the previous one are
explicitly noted. If a particular release is not listed, its libstdc++.so binary has the same filename and DT_SONAME as the
preceding release.
It is versioned as follows:
• GCC 3.0.0: libstdc++.so.3.0.0
• GCC 3.0.1: libstdc++.so.3.0.1
• GCC 3.0.2: libstdc++.so.3.0.2
• GCC 3.0.3: libstdc++.so.3.0.2 (See Note 1)

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• GCC 3.0.4: libstdc++.so.3.0.4
• GCC 3.1.0: libstdc++.so.4.0.0 (Incompatible with previous)
• GCC 3.1.1: libstdc++.so.4.0.1
• GCC 3.2.0: libstdc++.so.5.0.0 (Incompatible with previous)
• GCC 3.2.1: libstdc++.so.5.0.1
• GCC 3.2.2: libstdc++.so.5.0.2
• GCC 3.2.3: libstdc++.so.5.0.3 (See Note 2)
• GCC 3.3.0: libstdc++.so.5.0.4
• GCC 3.3.1: libstdc++.so.5.0.5
• GCC 3.4.0: libstdc++.so.6.0.0 (Incompatible with previous)
• GCC 3.4.1: libstdc++.so.6.0.1
• GCC 3.4.2: libstdc++.so.6.0.2
• GCC 3.4.3: libstdc++.so.6.0.3
• GCC 4.0.0: libstdc++.so.6.0.4
• GCC 4.0.1: libstdc++.so.6.0.5
• GCC 4.0.2: libstdc++.so.6.0.6
• GCC 4.0.3: libstdc++.so.6.0.7
• GCC 4.1.0: libstdc++.so.6.0.7
• GCC 4.1.1: libstdc++.so.6.0.8
• GCC 4.2.0: libstdc++.so.6.0.9
• GCC 4.2.1: libstdc++.so.6.0.9 (See Note 3)
• GCC 4.2.2: libstdc++.so.6.0.9
• GCC 4.3.0: libstdc++.so.6.0.10
• GCC 4.4.0: libstdc++.so.6.0.11
• GCC 4.4.1: libstdc++.so.6.0.12
• GCC 4.4.2: libstdc++.so.6.0.13
• GCC 4.5.0: libstdc++.so.6.0.14
• GCC 4.6.0: libstdc++.so.6.0.15
• GCC 4.6.1: libstdc++.so.6.0.16
• GCC 4.7.0: libstdc++.so.6.0.17
• GCC 4.8.0: libstdc++.so.6.0.18
• GCC 4.8.3: libstdc++.so.6.0.19
• GCC 4.9.0: libstdc++.so.6.0.20
• GCC 5.1.0: libstdc++.so.6.0.21
• GCC 6.1.0: libstdc++.so.6.0.22
• GCC 7.1.0: libstdc++.so.6.0.23
• GCC 7.2.0: libstdc++.so.6.0.24
Note 1: Error should be libstdc++.so.3.0.3.
Note 2: Not strictly required.
Note 3: This release (but not previous or subsequent) has one known incompatibility, see 33678 in the GCC bug database.

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4. Symbol versioning on the libstdc++.so binary.
mapfile: libstdc++-v3/config/abi/pre/gnu.ver
It is versioned with the following labels and version definitions, where the version definition is the maximum for a particular
release. Note, only symbols which are newly introduced will use the maximum version definition. Thus, for release series
with the same label, but incremented version definitions, the later release has both versions. (An example of this would be
the GCC 3.2.1 release, which has GLIBCPP_3.2.1 for new symbols and GLIBCPP_3.2 for symbols that were introduced
in the GCC 3.2.0 release.) If a particular release is not listed, it has the same version labels as the preceding release.
• GCC 3.0.0: (Error, not versioned)
• GCC 3.0.1: (Error, not versioned)
• GCC 3.0.2: (Error, not versioned)
• GCC 3.0.3: (Error, not versioned)
• GCC 3.0.4: (Error, not versioned)
• GCC 3.1.0: GLIBCPP_3.1, CXXABI_1
• GCC 3.1.1: GLIBCPP_3.1, CXXABI_1
• GCC 3.2.0: GLIBCPP_3.2, CXXABI_1.2
• GCC 3.2.1: GLIBCPP_3.2.1, CXXABI_1.2
• GCC 3.2.2: GLIBCPP_3.2.2, CXXABI_1.2
• GCC 3.2.3: GLIBCPP_3.2.2, CXXABI_1.2
• GCC 3.3.0: GLIBCPP_3.2.2, CXXABI_1.2.1
• GCC 3.3.1: GLIBCPP_3.2.3, CXXABI_1.2.1
• GCC 3.3.2: GLIBCPP_3.2.3, CXXABI_1.2.1
• GCC 3.3.3: GLIBCPP_3.2.3, CXXABI_1.2.1
• GCC 3.4.0: GLIBCXX_3.4, CXXABI_1.3
• GCC 3.4.1: GLIBCXX_3.4.1, CXXABI_1.3
• GCC 3.4.2: GLIBCXX_3.4.2
• GCC 3.4.3: GLIBCXX_3.4.3
• GCC 4.0.0: GLIBCXX_3.4.4, CXXABI_1.3.1
• GCC 4.0.1: GLIBCXX_3.4.5
• GCC 4.0.2: GLIBCXX_3.4.6
• GCC 4.0.3: GLIBCXX_3.4.7
• GCC 4.1.1: GLIBCXX_3.4.8
• GCC 4.2.0: GLIBCXX_3.4.9
• GCC 4.3.0: GLIBCXX_3.4.10, CXXABI_1.3.2
• GCC 4.4.0: GLIBCXX_3.4.11, CXXABI_1.3.3
• GCC 4.4.1: GLIBCXX_3.4.12, CXXABI_1.3.3
• GCC 4.4.2: GLIBCXX_3.4.13, CXXABI_1.3.3
• GCC 4.5.0: GLIBCXX_3.4.14, CXXABI_1.3.4
• GCC 4.6.0: GLIBCXX_3.4.15, CXXABI_1.3.5
• GCC 4.6.1: GLIBCXX_3.4.16, CXXABI_1.3.5
• GCC 4.7.0: GLIBCXX_3.4.17, CXXABI_1.3.6
• GCC 4.8.0: GLIBCXX_3.4.18, CXXABI_1.3.7
• GCC 4.8.3: GLIBCXX_3.4.19, CXXABI_1.3.7
• GCC 4.9.0: GLIBCXX_3.4.20, CXXABI_1.3.8
• GCC 5.1.0: GLIBCXX_3.4.21, CXXABI_1.3.9

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• GCC 6.1.0: GLIBCXX_3.4.22, CXXABI_1.3.10
• GCC 7.1.0: GLIBCXX_3.4.23, CXXABI_1.3.11
• GCC 7.2.0: GLIBCXX_3.4.24, CXXABI_1.3.11
5. Incremental bumping of a compiler pre-defined macro, __GXX_ABI_VERSION. This macro is defined as the version of
the compiler v3 ABI, with g++ 3.0 being version 100. This macro will be automatically defined whenever g++ is used (the
curious can test this by invoking g++ with the ’-v’ flag.)
This macro was defined in the file "lang-specs.h" in the gcc/cp directory. Later versions defined it in "c-common.c" in the
gcc directory, and from G++ 3.4 it is defined in c-cppbuiltin.c and its value determined by the ’-fabi-version’ command
line option.
It is versioned as follows, where ’n’ is given by ’-fabi-version=n’:
• GCC 3.0: 100
• GCC 3.1: 100 (Error, should be 101)
• GCC 3.2: 102
• GCC 3.3: 102
• GCC 3.4, GCC 4.x: 102 (when n=1)
• GCC 3.4, GCC 4.x: 1000 + n (when n>1)
• GCC 3.4, GCC 4.x: 999999 (when n=0)
6. Changes to the default compiler option for -fabi-version.
It is versioned as follows:
• GCC 3.0: (Error, not versioned)
• GCC 3.1: (Error, not versioned)
• GCC 3.2: -fabi-version=1
• GCC 3.3: -fabi-version=1
• GCC 3.4, GCC 4.x: -fabi-version=2 (Incompatible with previous)
• GCC 5 and higher: -fabi-version=0 (See GCC manual for meaning)
7. Incremental bumping of a library pre-defined macro. For releases before 3.4.0, the macro is __GLIBCPP__. For later
releases, it’s __GLIBCXX__. (The libstdc++ project generously changed from CPP to CXX throughout its source to
allow the "C" pre-processor the CPP macro namespace.) These macros are defined as the date the library was released, in
compressed ISO date format, as an integer constant.
This macro is defined in the file c++config in the libstdc++-v3/include/bits directory. Up to GCC 4.1.0,
it was changed every night by an automated script. Since GCC 4.1.0 it is set during configuration to the same value as
gcc/DATESTAMP, so for an official release its value is the same as the date of the release, which is given in the GCC
Release Timeline.
This macro can be used in code to detect whether the C++ Standard Library implementation in use is libstdc++, but is not
useful for detecting the libstdc++ version, nor whether particular features are supported. The macro value might be a date
after a feature was added to the development trunk, but the release could be from an older branch without the feature. For
example, in the 5.4.0 release the macro has the value 20160603 which is greater than the 20160427 value of the macro
in the 6.1.0 release, but there are features supported in the 6.1.0 release that are not supported in 5.4.0 release. You also
can’t test for the exact values listed below to try and identify a release, because a snapshot taken from the gcc-5-branch
on 2016-04-27 would have the same value for the macro as the 6.1.0 release despite being a different version. Many
GNU/Linux distributions build their GCC packages from snapshots, so the macro can have dates that don’t correspond to
official releases.
It is versioned as follows:
• GCC 3.0.0: 20010615
• GCC 3.0.1: 20010819

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• GCC 3.0.2: 20011023
• GCC 3.0.3: 20011220
• GCC 3.0.4: 20020220
• GCC 3.1.0: 20020514
• GCC 3.1.1: 20020725
• GCC 3.2.0: 20020814
• GCC 3.2.1: 20021119
• GCC 3.2.2: 20030205
• GCC 3.2.3: 20030422
• GCC 3.3.0: 20030513
• GCC 3.3.1: 20030804
• GCC 3.3.2: 20031016
• GCC 3.3.3: 20040214
• GCC 3.4.0: 20040419
• GCC 3.4.1: 20040701
• GCC 3.4.2: 20040906
• GCC 3.4.3: 20041105
• GCC 3.4.4: 20050519
• GCC 3.4.5: 20051201
• GCC 3.4.6: 20060306
• GCC 4.0.0: 20050421
• GCC 4.0.1: 20050707
• GCC 4.0.2: 20050921
• GCC 4.0.3: 20060309
• GCC 4.1.0 and later: the GCC release date, as shown in the GCC Release Timeline
8. Since GCC 7, incremental bumping of a library pre-defined macro, _GLIBCXX_RELEASE. This macro is defined to the
GCC major version that the libstdc++ headers belong to, as an integer constant. When compiling with GCC it has the same
value as GCC’s pre-defined macro __GNUC__. This macro can be used when libstdc++ is used with a non-GNU compiler
where __GNUC__ is not defined, or has a different value that doesn’t correspond to the libstdc++ version.
This macro is defined in the file c++config in the libstdc++-v3/include/bits directory and is generated automatically by autoconf as part of the configure-time generation of config.h and subsequently .
9. Historically, incremental bumping of a library pre-defined macro, _GLIBCPP_VERSION. This macro was defined as the
released version of the library, as a string literal. This was only implemented in GCC 3.1.0 releases and higher, and was
deprecated in 3.4.x (where it was called _GLIBCXX_VERSION), and is not defined in 4.0.0 and higher.
This macro is defined in the same file as _GLIBCXX_RELEASE, described above.
It is versioned as follows:
• GCC 3.0.0: "3.0.0"
• GCC 3.0.1: "3.0.0" (Error, should be "3.0.1")
• GCC 3.0.2: "3.0.0" (Error, should be "3.0.2")
• GCC 3.0.3: "3.0.0" (Error, should be "3.0.3")
• GCC 3.0.4: "3.0.0" (Error, should be "3.0.4")
• GCC 3.1.0: "3.1.0"
• GCC 3.1.1: "3.1.1"
• GCC 3.2.0: "3.2"

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• GCC 3.2.1: "3.2.1"
• GCC 3.2.2: "3.2.2"
• GCC 3.2.3: "3.2.3"
• GCC 3.3.0: "3.3"
• GCC 3.3.1: "3.3.1"
• GCC 3.3.2: "3.3.2"
• GCC 3.3.3: "3.3.3"
• GCC 3.4: "version-unused"
• GCC 4 and later: not defined
10. Matching each specific C++ compiler release to a specific set of C++ include files. This is only implemented in GCC 3.1.1
releases and higher.
All C++ includes are installed in include/c++, then nested in a directory hierarchy corresponding to the C++ compiler’s
released version. This version corresponds to the variable "gcc_version" in "libstdc++-v3/acinclude.m4," and more details
can be found in that file’s macro GLIBCXX_CONFIGURE (GLIBCPP_CONFIGURE before GCC 3.4.0).
C++ includes are versioned as follows:
• GCC 3.0.0: include/g++-v3
• GCC 3.0.1: include/g++-v3
• GCC 3.0.2: include/g++-v3
• GCC 3.0.3: include/g++-v3
• GCC 3.0.4: include/g++-v3
• GCC 3.1.0: include/g++-v3
• GCC 3.1.1: include/c++/3.1.1
• GCC 3.2.0: include/c++/3.2
• GCC 3.2.1: include/c++/3.2.1
• GCC 3.2.2: include/c++/3.2.2
• GCC 3.2.3: include/c++/3.2.3
• GCC 3.3.0: include/c++/3.3
• GCC 3.3.1: include/c++/3.3.1
• GCC 3.3.2: include/c++/3.3.2
• GCC 3.3.3: include/c++/3.3.3
• GCC 3.4.x: include/c++/3.4.x
• GCC 4.x.y: include/c++/4.x.y
• GCC 5.x.0: include/c++/5.x.0
Taken together, these techniques can accurately specify interface and implementation changes in the GNU C++ tools themselves. Used properly, they allow both the GNU C++ tools implementation, and programs using them, an evolving yet controlled
development that maintains backward compatibility.
B.5.2.3

Prerequisites

Minimum environment that supports a versioned ABI: A supported dynamic linker, a GNU linker of sufficient vintage to understand demangled C++ name globbing (ld) or the Sun linker, a shared executable compiled with g++, and shared libraries
(libgcc_s, libstdc++) compiled by a compiler (g++) with a compatible ABI. Phew.
On top of all that, an additional constraint: libstdc++ did not attempt to version symbols (or age gracefully, really) until version
3.1.0.
Most modern GNU/Linux and BSD versions, particularly ones using GCC 3.1 and later, will meet the requirements above, as
does Solaris 2.5 and up.

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Configuring

It turns out that most of the configure options that change default behavior will impact the mangled names of exported symbols,
and thus impact versioning and compatibility.
For more information on configure options, including ABI impacts, see: here
There is one flag that explicitly deals with symbol versioning: --enable-symvers.
In particular, libstdc++-v3/acinclude.m4 has a macro called GLIBCXX_ENABLE_SYMVERS that defaults to yes (or the argument passed in via --enable-symvers=foo). At that point, the macro attempts to make sure that all the requirement for symbol
versioning are in place. For more information, please consult acinclude.m4.
B.5.2.5

Checking Active

When the GNU C++ library is being built with symbol versioning on, you should see the following at configure time for libstdc++
(showing either ’gnu’ or another of the supported styles):
checking versioning on shared library symbols... gnu

If you don’t see this line in the configure output, or if this line appears but the last word is ’no’, then you are out of luck.
If the compiler is pre-installed, a quick way to test is to compile the following (or any) simple C++ file and link it to the shared
libstdc++ library:
#include 
int main()
{ std::cout << "hello" << std::endl; return 0; }
%g++ hello.cc -o hello.out
%ldd hello.out
libstdc++.so.5 => /usr/lib/libstdc++.so.5 (0x00764000)
libm.so.6 => /lib/tls/libm.so.6 (0x004a8000)
libgcc_s.so.1 => /mnt/hd/bld/gcc/gcc/libgcc_s.so.1 (0x40016000)
libc.so.6 => /lib/tls/libc.so.6 (0x0036d000)
/lib/ld-linux.so.2 => /lib/ld-linux.so.2 (0x00355000)
%nm hello.out

If you see symbols in the resulting output with "GLIBCXX_3" as part of the name, then the executable is versioned. Here’s an
example:
U _ZNSt8ios_base4InitC1Ev@@GLIBCXX_3.4
On Solaris 2, you can use pvs -r instead:
%g++ hello.cc -o hello.out
%pvs -r hello.out
libstdc++.so.6 (GLIBCXX_3.4, GLIBCXX_3.4.12);
libgcc_s.so.1 (GCC_3.0);
libc.so.1 (SUNWprivate_1.1, SYSVABI_1.3);

ldd -v works too, but is very verbose.

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Allowed Changes

The following will cause the library minor version number to increase, say from "libstdc++.so.3.0.4" to "libstdc++.so.3.0.5".
1. Adding an exported global or static data member
2. Adding an exported function, static or non-virtual member function
3. Adding an exported symbol or symbols by additional instantiations
Other allowed changes are possible.

B.5.4

Prohibited Changes

The following non-exhaustive list will cause the library major version number to increase, say from "libstdc++.so.3.0.4" to
"libstdc++.so.4.0.0".
1. Changes in the gcc/g++ compiler ABI
2. Changing size of an exported symbol
3. Changing alignment of an exported symbol
4. Changing the layout of an exported symbol
5. Changing mangling on an exported symbol
6. Deleting an exported symbol
7. Changing the inheritance properties of a type by adding or removing base classes
8. Changing the size, alignment, or layout of types specified in the C++ standard. These may not necessarily be instantiated or otherwise exported in the library binary, and include all the required locale facets, as well as things like
std::basic_streambuf, et al.
9. Adding an explicit copy constructor or destructor to a class that would otherwise have implicit versions. This will change
the way the compiler deals with this class in by-value return statements or parameters: instead of passing instances of this
class in registers, the compiler will be forced to use memory. See the section on Function Calling Conventions and APIs
of the C++ ABI documentation for further details.

B.5.5

Implementation

1. Separation of interface and implementation
This is accomplished by two techniques that separate the API from the ABI: forcing undefined references to link against a
library binary for definitions.
Include files have declarations, source files have defines For non-templatized types, such as much of class locale,
the appropriate standard C++ include, say locale, can contain full declarations, while various source files (say
locale.cc, locale_init.cc, localename.cc) contain definitions.
Extern template on required types For parts of the standard that have an explicit list of required instantiations, the GNU
extension syntax extern template can be used to control where template definitions reside. By marking
required instantiations as extern template in include files, and providing explicit instantiations in the appropriate instantiation files, non-inlined template functions can be versioned. This technique is mostly used on parts of
the standard that require char and wchar_t instantiations, and includes basic_string, the locale facets,
and the types in iostreams.
In addition, these techniques have the additional benefit that they reduce binary size, which can increase runtime performance.

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2. Namespaces linking symbol definitions to export mapfiles
All symbols in the shared library binary are processed by a linker script at build time that either allows or disallows external
linkage. Because of this, some symbols, regardless of normal C/C++ linkage, are not visible. Symbols that are internal
have several appealing characteristics: by not exporting the symbols, there are no relocations when the shared library is
started and thus this makes for faster runtime loading performance by the underlying dynamic loading mechanism. In
addition, they have the possibility of changing without impacting ABI compatibility.
The following namespaces are transformed by the mapfile:
namespace std Defaults to exporting all symbols in label GLIBCXX that do not begin with an underscore, i.e., __te
st_func would not be exported by default. Select exceptional symbols are allowed to be visible.
namespace __gnu_cxx Defaults to not exporting any symbols in label GLIBCXX, select items are allowed to be
visible.
namespace __gnu_internal Defaults to not exported, no items are allowed to be visible.
namespace __cxxabiv1, aliased to namespace abi Defaults to not exporting any symbols in label CXXABI,
select items are allowed to be visible.
3. Freezing the API
Disallowed changes, as above, are not made on a stable release branch. Enforcement tends to be less strict with GNU
extensions that standard includes.

B.5.6

Testing

B.5.6.1

Single ABI Testing

Testing for GNU C++ ABI changes is composed of two distinct areas: testing the C++ compiler (g++) for compiler changes, and
testing the C++ library (libstdc++) for library changes.
Testing the C++ compiler ABI can be done various ways.
One. Intel ABI checker.
Two. The second is yet unreleased, but has been announced on the gcc mailing list. It is yet unspecified if these tools will be
freely available, and able to be included in a GNU project. Please contact Mark Mitchell (mark@codesourcery.com) for more
details, and current status.
Three. Involves using the vlad.consistency test framework. This has also been discussed on the gcc mailing lists.
Testing the C++ library ABI can also be done various ways.
One. (Brendan Kehoe, Jeff Law suggestion to run ’make check-c++’ two ways, one with a new compiler and an old library, and
the other with an old compiler and a new library, and look for testsuite regressions)
Details on how to set this kind of test up can be found here: http://gcc.gnu.org/ml/gcc/2002-08/msg00142.html
Two. Use the ’make check-abi’ rule in the libstdc++ Makefile.
This is a proactive check of the library ABI. Currently, exported symbol names that are either weak or defined are checked against
a last known good baseline. Currently, this baseline is keyed off of 3.4.0 binaries, as this was the last time the .so number was
incremented. In addition, all exported names are demangled, and the exported objects are checked to make sure they are the
same size as the same object in the baseline. Notice that each baseline is relative to a default configured library and compiler: in
particular, if options such as --enable-clocale, or --with-cpu, in case of multilibs, are used at configure time, the check may fail,
either because of substantive differences or because of limitations of the current checking machinery.
This dataset is insufficient, yet a start. Also needed is a comprehensive check for all user-visible types part of the standard library
for sizeof() and alignof() changes.
Verifying compatible layouts of objects is not even attempted. It should be possible to use sizeof, alignof, and offsetof to compute
offsets for each structure and type in the standard library, saving to another datafile. Then, compute this in a similar way for new
binaries, and look for differences.
Another approach might be to use the -fdump-class-hierarchy flag to get information. However, currently this approach gives
insufficient data for use in library testing, as class data members, their offsets, and other detailed data is not displayed with this
flag. (See PR g++/7470 on how this was used to find bugs.)
Perhaps there are other C++ ABI checkers. If so, please notify us. We’d like to know about them!

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Multiple ABI Testing

A "C" application, dynamically linked to two shared libraries, liba, libb. The dependent library liba is a C++ shared library
compiled with GCC 3.3, and uses io, exceptions, locale, etc. The dependent library libb is a C++ shared library compiled with
GCC 3.4, and also uses io, exceptions, locale, etc.
As above, libone is constructed as follows:
%$bld/H-x86-gcc-3.4.0/bin/g++ -fPIC -DPIC -c a.cc
%$bld/H-x86-gcc-3.4.0/bin/g++ -shared -Wl,-soname -Wl,libone.so.1 -Wl,-O1 -Wl,-z,defs a.o - ←o libone.so.1.0.0
%ln -s libone.so.1.0.0 libone.so
%$bld/H-x86-gcc-3.4.0/bin/g++ -c a.cc
%ar cru libone.a a.o

And, libtwo is constructed as follows:
%$bld/H-x86-gcc-3.3.3/bin/g++ -fPIC -DPIC -c b.cc
%$bld/H-x86-gcc-3.3.3/bin/g++ -shared -Wl,-soname -Wl,libtwo.so.1 -Wl,-O1 -Wl,-z,defs b.o - ←o libtwo.so.1.0.0
%ln -s libtwo.so.1.0.0 libtwo.so
%$bld/H-x86-gcc-3.3.3/bin/g++ -c b.cc
%ar cru libtwo.a b.o

...with the resulting libraries looking like
%ldd libone.so.1.0.0
libstdc++.so.6 => /usr/lib/libstdc++.so.6 (0x40016000)
libm.so.6 => /lib/tls/libm.so.6 (0x400fa000)
libgcc_s.so.1 => /mnt/hd/bld/gcc/gcc/libgcc_s.so.1 (0x4011c000)
libc.so.6 => /lib/tls/libc.so.6 (0x40125000)
/lib/ld-linux.so.2 => /lib/ld-linux.so.2 (0x00355000)
%ldd libtwo.so.1.0.0
libstdc++.so.5 => /usr/lib/libstdc++.so.5 (0x40027000)
libm.so.6 => /lib/tls/libm.so.6 (0x400e1000)
libgcc_s.so.1 => /mnt/hd/bld/gcc/gcc/libgcc_s.so.1 (0x40103000)
libc.so.6 => /lib/tls/libc.so.6 (0x4010c000)
/lib/ld-linux.so.2 => /lib/ld-linux.so.2 (0x00355000)

Then, the "C" compiler is used to compile a source file that uses functions from each library.
gcc test.c -g -O2 -L. -lone -ltwo /usr/lib/libstdc++.so.5 /usr/lib/libstdc++.so.6

Which gives the expected:
%ldd a.out
libstdc++.so.5 => /usr/lib/libstdc++.so.5 (0x00764000)
libstdc++.so.6 => /usr/lib/libstdc++.so.6 (0x40015000)
libc.so.6 => /lib/tls/libc.so.6 (0x0036d000)
libm.so.6 => /lib/tls/libm.so.6 (0x004a8000)

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libgcc_s.so.1 => /mnt/hd/bld/gcc/gcc/libgcc_s.so.1 (0x400e5000)
/lib/ld-linux.so.2 => /lib/ld-linux.so.2 (0x00355000)

This resulting binary, when executed, will be able to safely use code from both liba, and the dependent libstdc++.so.6, and libb,
with the dependent libstdc++.so.5.

B.5.7

Outstanding Issues

Some features in the C++ language make versioning especially difficult. In particular, compiler generated constructs such as
implicit instantiations for templates, typeinfo information, and virtual tables all may cause ABI leakage across shared library
boundaries. Because of this, mixing C++ ABIs is not recommended at this time.
For more background on this issue, see these bugzilla entries:
24660: versioning weak symbols in libstdc++
19664: libstdc++ headers should have pop/push of the visibility around the declarations

B.5.8

Bibliography
[99] ABIcheck
[100] Itanium C++ ABI
[101] Intel Compilers for Linux: Compatibility with GNU Compilers
[102] Linker and Libraries Guide (document 819-0690)
[103] Sun Studio 11: C++ Migration Guide (document 819-3689)
[104] Ulrich Drepper, How to Write Shared Libraries
[105] C++ ABI for the ARM Architecture
[106] Benjamin Kosnik, Dynamic Shared Objects: Survey and Issues , ISO C++ J16/06-0046 .
[107] Benjamin Kosnik, Versioning With Namespaces , ISO C++ J16/06-0083 .
[108] Pavel ShvedDenis Silakov, Binary Compatibility of Shared Libraries Implemented in C++ on GNU/Linux
Systems , SYRCoSE 2009 .

B.6

API Evolution and Deprecation History

A list of user-visible changes, in chronological order

B.6.1 3.0
Extensions moved to include/ext.
Include files from the SGI/HP sources that pre-date the ISO standard are added. These files are placed into the include/
backward directory and a deprecated warning is added that notifies on inclusion (-Wno-deprecated deactivates the warning.)
Deprecated include backward/strstream added.
Removal of include builtinbuf.h, indstream.h, parsestream.h, PlotFile.h, SFile.h, stdiostream.h,
and stream.h.

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B.6.2 3.1
Extensions from SGI/HP moved from namespace std to namespace __gnu_cxx. As part of this, the following new
includes are added: ext/algorithm, ext/functional, ext/iterator, ext/memory, and ext/numeric.
Extensions to basic_filebuf introduced: __gnu_cxx::enc_filebuf, and __gnu_cxx::stdio_filebuf.
Extensions to tree data structures added in ext/rb_tree.
Removal of ext/tree, moved to backward/tree.h.

B.6.3 3.2
Symbol versioning introduced for shared library.
Removal of include backward/strstream.h.
Allocator changes. Change __malloc_alloc to malloc_allocator and __new_alloc to new_allocator.
For GCC releases from 2.95 through the 3.1 series, defining __USE_MALLOC on the gcc command line would change the
default allocation strategy to instead use malloc and free. For the 3.2 and 3.3 release series the same functionality was
spelled _GLIBCXX_FORCE_NEW. From GCC 3.4 onwards the functionality is enabled by setting GLIBCXX_FORCE_NEW in
the environment, see the mt allocator chapter for details.
Error handling in iostreams cleaned up, made consistent.

B.6.4 3.3
B.6.5 3.4
Large file support.
Extensions for generic characters and char_traits added in ext/pod_char_traits.h.
Support for wchar_t specializations of basic_filebuf enhanced to support UTF-8 and Unicode, depending on host.
More hosts support basic wchar_t functionality.
Support for char_traits beyond builtin types.

Conformant allocator class and usage in containers. As part of this, the following extensions are added: ext/bitmap_
allocator.h, ext/debug_allocator.h, ext/mt_allocator.h, ext/malloc_allocator.h,ext/new_allocato
h, ext/pool_allocator.h.
This is a change from all previous versions, and may require source-level changes due to allocator-related changes to structures
names and template parameters, filenames, and file locations. Some, like __simple_alloc, __allocator, __alloc,
and _Alloc_traits have been removed.
Default behavior of std::allocator has changed.
Previous versions prior to 3.4 cache allocations in a memory pool, instead of passing through to call the global allocation operators
(i.e., __gnu_cxx::pool_allocator). More recent versions default to the simpler __gnu_cxx::new_allocator.
Previously, all allocators were written to the SGI style, and all STL containers expected this interface. This interface had
a traits class called _Alloc_traits that attempted to provide more information for compile-time allocation selection and
optimization. This traits class had another allocator wrapper, __simple_alloc, which was a wrapper around another
allocator, A, which itself is an allocator for instances of T. But wait, there’s more: __allocator is another adapter.
Many of the provided allocator classes were SGI style: such classes can be changed to a conforming interface with this wrapper:
__allocator is thus the same as allocator.
The class allocator used the typedef __alloc to select an underlying allocator that satisfied memory allocation requests. The
selection of this underlying allocator was not user-configurable.
Releases after gcc-3.4 have continued to add to the collection of available allocators. All of these new allocators are standardstyle. The following table includes details, along with the first released version of GCC that included the extension allocator.

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Allocator (3.4)
__gnu_cxx::
new_allocator
__gnu_cxx::malloc_
allocator
__gnu_cxx::
debug_allocator

Header (3.4)
ext/new_allocator.
h
ext/malloc_
allocator.h
ext/debug_
allocator.h

__gnu_cxx::
__pool_alloc

ext/pool_
allocator.h

__gnu_cxx::
__mt_alloc
__gnu_cxx::bitmap_
allocator

Allocator (3.[0-3])

Header (3.[0-3])

std::__new_alloc

memory

std::__malloc_allo
c_template
std::
debug_alloc
std::
__default_alloc_te
mplate

memory
memory
memory

ext/mt_allocator.h
ext/bitmap_
allocator.h
Table B.6: Extension Allocators

Allocator
__gnu_cxx::
array_allocator
__gnu_cxx::
throw_allocator

Include

Version

ext/array_allocator.h

4.0.0

ext/throw_allocator.h

4.2.0

Table B.7: Extension Allocators Continued
Debug mode first appears.
Precompiled header support PCH support.
Macro guard for changed, from _GLIBCPP_ to _GLIBCXX_.
Extension ext/stdio_sync_filebuf.h added.
Extension ext/demangle.h added.

B.6.6 4.0
TR1 features first appear.
Extension allocator ext/array_allocator.h added.
Extension codecvt specializations moved to ext/codecvt_specializations.h.
Removal of ext/demangle.h.

B.6.7 4.1
Removal of cassert from all standard headers: now has to be explicitly included for std::assert calls.
Extensions for policy-based data structures first added. New includes, types, namespace pb_assoc.
Extensions for typelists added in ext/typelist.h.
Extension for policy-based basic_string first added: __gnu_cxx::__versa_string in ext/vstring.h.

B.6.8 4.2
Default visibility attributes applied to namespace std. Support for -fvisibility.

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TR1 random, complex, and C compatibility headers added.
Extensions for concurrent programming consolidated into ext/concurrence.h and ext/atomicity.h, including change
of namespace to __gnu_cxx in some cases. Added types include _Lock_policy, __concurrence_lock_error,
__concurrence_unlock_error, __mutex, __scoped_lock.
Extensions for type traits consolidated into ext/type_traits.h. Additional traits are added (__conditional_type,
__enable_if, others.)
Extensions for policy-based data structures revised. New includes, types, namespace moved to __pb_ds.
Extensions for debug mode modified: now nested in namespace std::__debug and extensions in namespace __gnu_
cxx::__debug.
Extensions added: ext/typelist.h and ext/throw_allocator.h.

B.6.9 4.3
C++0X features first appear.
TR1 regex and cmath’s mathematical special function added.
Backward include edit.
• Removed
algobase.h algo.h alloc.h bvector.h complex.h defalloc.h deque.h fstream.h function.h hash_
map.h hash_set.h hashtable.h heap.h iomanip.h iostream.h istream.h iterator.h list.h map.h
multimap.h multiset.h new.h ostream.h pair.h queue.h rope.h set.h slist.h stack.h streambuf.
h stream.h tempbuf.h tree.h vector.h
• Added
hash_map and hash_set
• Added in C++11
auto_ptr.h and binders.h
Header dependency streamlining.
• algorithm no longer includes climits, cstring, or iosfwd
• bitset no longer includes istream or ostream, adds iosfwd
• functional no longer includes cstddef
• iomanip no longer includes istream, istream, or functional, adds ioswd
• numeric no longer includes iterator
• string no longer includes algorithm or memory
• valarray no longer includes numeric or cstdlib
• tr1/hashtable no longer includes memory or functional
• tr1/memory no longer includes algorithm
• tr1/random no longer includes algorithm or fstream
Debug mode for unordered_map and unordered_set.
Parallel mode first appears.
Variadic template implementations of items in tuple and functional.
Default what implementations give more elaborate exception strings for bad_cast, bad_typeid, bad_exception, and
bad_alloc.
PCH binary files no longer installed. Instead, the source files are installed.
Namespace pb_ds moved to __gnu_pb_ds.

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B.6.10 4.4
C++0X features.
• Added.
atomic, chrono, condition_variable, forward_list, initializer_list, mutex, ratio, thread
• Updated and improved.
algorithm, system_error, type_traits
• Use of the GNU extension namespace association converted to inline namespaces.
• Preliminary support for initializer_list and defaulted and deleted constructors in container classes.
• unique_ptr.
• Support for new character types char16_t and char32_t added to char_traits, basic_string, numeric_limits,
and assorted compile-time type traits.
• Support for string conversions to_string and to_wstring.
• Member functions taking string arguments were added to iostreams including basic_filebuf, basic_ofstream, and
basic_ifstream.
• Exception propagation support, including exception_ptr, current_exception, copy_exception, and rethro
w_exception.
Uglification of try to __try and catch to __catch.
Audit of internal mutex usage, conversion to functions returning static local mutex.
Extensions added: ext/pointer.h and ext/extptr_allocator.h. Support for non-standard pointer types has been
added to vector and forward_list.

B.6.11 4.5
C++0X features.
• Added.
functional, future, random
• Updated and improved.
atomic, system_error, type_traits
• Add support for explicit operators and standard layout types.
Profile mode first appears.
Support for decimal floating-point arithmetic, including decimal32, decimal64, and decimal128.
Python pretty-printers are added for use with appropriately-advanced versions of gdb.
Audit for application of function attributes nothrow, const, pure, and noreturn.
The default behavior for comparing typeinfo names changed, so in typeinfo, __GXX_MERGED_TYPEINFO_NAMES now
defaults to zero.
Extensions modified: ext/throw_allocator.h.

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B.6.12 4.6
Use constexpr and nullptr where appropriate throughout the library.
The library was updated to avoid including stddef.h in order to reduce namespace pollution.
Reference-count annotations to assist data race detectors.
Added make_exception_ptr as an alias of copy_exception.

B.6.13 4.7
Use of noexcept throughout library.
Partial support for C++11 allocators first appears.
monotonic_clock renamed to steady_clock as required by the final C++11 standard.
A new clocale model for newlib is available.
The library was updated to avoid including unistd.h in order to reduce namespace pollution.
Debug Mode was improved for unordered containers.

B.6.14 4.8
New random number engines and distributions. Optimisations for random.
New --enable-libstdcxx-verbose configure option
The --enable-libstdcxx-time configure option becomes unnecessary given a sufficiently recent glibc.

B.6.15 4.9
Implementation of regex completed.
C++14 library and TS implementations are added.
copy_exception deprecated.
__gnu_cxx::array_allocator deprecated.

B.6.16 5
ABI transition adds new implementations of several components, using the abi_tag attribute and the __cxx11 inline namespace to distinguish the new entities from the old ones.
• Use of the new or old ABI can be selected per-translation unit with the _GLIBCXX_USE_CXX11_ABI macro.
• New non-reference-counted string implementation.
• New list implementation containing a new data member in order to provide O(1) size().
C++11 support completed (movable iostreams, new I/O manipulators, Unicode conversion utilities, atomic operations for shar
ed_ptr, functions for notifying condition variables and making futures ready at thread exit).
Changed formatting of floating point types when ios_base::fixed|ios_base::scientific is set in a stream’s format
flags.
Improved C++14 support and TS implementations.
New random number engines and distributions.
GDB Xmethods for containers and unique_ptr added.
has_trivial_default_constructor, has_trivial_copy_constructor and has_trivial_copy_assign
deprecated.

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Backwards Compatibility
First

The first generation GNU C++ library was called libg++. It was a separate GNU project, although reliably paired with GCC.
Rumors imply that it had a working relationship with at least two kinds of dinosaur.
Some background: libg++ was designed and created when there was no ISO standard to provide guidance. Classes like linked
lists are now provided for by list and do not need to be created by genclass. (For that matter, templates exist now and
are well-supported, whereas genclass (mostly) predates them.)
There are other classes in libg++ that are not specified in the ISO Standard (e.g., statistical analysis). While there are a lot of
really useful things that are used by a lot of people, the Standards Committee couldn’t include everything, and so a lot of those
“obvious” classes didn’t get included.
Known Issues include many of the limitations of its immediate ancestor.
Portability notes and known implementation limitations are as follows.
B.7.1.1

No ios_base

At least some older implementations don’t have std::ios_base, so you should use std::ios::badbit, std::ios::
failbit and std::ios::eofbit and std::ios::goodbit.
B.7.1.2

No cout in , no cin in 

In earlier versions of the standard, ,  and  used to define cout, cin and so on.
ISO C++ specifies that one needs to include  explicitly to get the required definitions.
Some include adjustment may be required.
This project is no longer maintained or supported, and the sources archived. For the desperate, the GCC extensions page describes
where to find the last libg++ source. The code is considered replaced and rewritten.

B.7.2

Second

The second generation GNU C++ library was called libstdc++, or libstdc++-v2. It spans the time between libg++ and pre-ISO
C++ standardization and is usually associated with the following GCC releases: egcs 1.x, gcc 2.95, and gcc 2.96.
The STL portions of this library are based on SGI/HP STL release 3.11.
This project is no longer maintained or supported, and the sources archived. The code is considered replaced and rewritten.
Portability notes and known implementation limitations are as follows.
B.7.2.1

Namespace std:: not supported

Some care is required to support C++ compiler and or library implementation that do not have the standard library in namespace
std.
The following sections list some possible solutions to support compilers that cannot ignore std::-qualified names.
First, see if the compiler has a flag for this. Namespace back-portability-issues are generally not a problem for g++ compilers
that do not have libstdc++ in std::, as the compilers use -fno-honor-std (ignore std::, ::=std::) by default. That
is, the responsibility for enabling or disabling std:: is on the user; the maintainer does not have to care about it. This probably
applies to some other compilers as well.
Second, experiment with a variety of pre-processor tricks.
By defining std as a macro, fully-qualified namespace calls become global. Volia.

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#ifdef WICKEDLY_OLD_COMPILER
# define std
#endif

Thanks to Juergen Heinzl who posted this solution on gnu.gcc.help.
Another pre-processor based approach is to define a macro NAMESPACE_STD, which is defined to either “ ” or “std” based on a
compile-type test. On GNU systems, this can be done with autotools by means of an autoconf test (see below) for HAVE_NAMESP
ACE_STD, then using that to set a value for the NAMESPACE_STD macro. At that point, one is able to use NAMESPACE_STD:
:string, which will evaluate to std::string or ::string (i.e., in the global namespace on systems that do not put
string in std::).
dnl @synopsis AC_CXX_NAMESPACE_STD
dnl
dnl If the compiler supports namespace std, define
dnl HAVE_NAMESPACE_STD.
dnl
dnl @category Cxx
dnl @author Todd Veldhuizen
dnl @author Luc Maisonobe 
dnl @version 2004-02-04
dnl @license AllPermissive
AC_DEFUN([AC_CXX_NAMESPACE_STD], [
AC_CACHE_CHECK(if g++ supports namespace std,
ac_cv_cxx_have_std_namespace,
[AC_LANG_SAVE
AC_LANG_CPLUSPLUS
AC_TRY_COMPILE([#include 
std::istream& is = std::cin;],,
ac_cv_cxx_have_std_namespace=yes, ac_cv_cxx_have_std_namespace=no)
AC_LANG_RESTORE
])
if test "$ac_cv_cxx_have_std_namespace" = yes; then
AC_DEFINE(HAVE_NAMESPACE_STD,,[Define if g++ supports namespace std. ])
fi
])

B.7.2.2

Illegal iterator usage

The following illustrate implementation-allowed illegal iterator use, and then correct use.
• you cannot do ostream::operator<<(iterator) to print the address of the iterator => use operator<< &*iter
ator instead
• you cannot clear an iterator’s reference (iterator =0) => use iterator =iterator_type();
• if (iterator) won’t work any more => use if (iterator !=iterator_type())
B.7.2.3 isspace from  is a macro

Glibc 2.0.x and 2.1.x define  functionality as macros (isspace, isalpha etc.).
This implementations of libstdc++, however, keep these functions as macros, and so it is not back-portable to use fully qualified
names. For example:
#include 
int main() { std::isspace(’X’); }

Results in something like this:

The GNU C++ Library Manual

369 / 399

std:: (__ctype_b[(int) ( ( ’X’ ) )] & (unsigned short int) _ISspace ) ;

A solution is to modify a header-file so that the compiler tells  to define functions instead of macros:
// This keeps isalnum, et al from being propagated as macros.
#if __linux__
# define __NO_CTYPE 1
#endif

Then, include 
Another problem arises if you put a using namespace std; declaration at the top, and include . This will
result in ambiguities between the definitions in the global namespace () and the definitions in namespace std::
().
B.7.2.4

No vector::at, deque::at, string::at

One solution is to add an autoconf-test for this:
AC_MSG_CHECKING(for container::at)
AC_TRY_COMPILE(
[
#include 
#include 
#include 
using namespace std;
],
[
deque test_deque(3);
test_deque.at(2);
vector test_vector(2);
test_vector.at(1);
string test_string(test_string);
test_string.at(3);
],
[AC_MSG_RESULT(yes)
AC_DEFINE(HAVE_CONTAINER_AT)],
[AC_MSG_RESULT(no)])

If you are using other (non-GNU) compilers it might be a good idea to check for string::at separately.
B.7.2.5

No std::char_traits::eof

Use some kind of autoconf test, plus this:
#ifdef HAVE_CHAR_TRAITS
#define CPP_EOF std::char_traits::eof()
#else
#define CPP_EOF EOF
#endif

B.7.2.6

No string::clear

There are two functions for deleting the contents of a string: clear and erase (the latter returns the string).
void
clear() { _M_mutate(0, this->size(), 0); }

The GNU C++ Library Manual

370 / 399

basic_string&
erase(size_type __pos = 0, size_type __n = npos)
{
return this->replace(_M_check(__pos), _M_fold(__pos, __n),
_M_data(), _M_data());
}

Unfortunately, clear is not implemented in this version, so you should use erase (which is probably faster than operator=
(charT*)).
B.7.2.7

Removal of ostream::form and istream::scan extensions

These are no longer supported. Please use stringstreams instead.
B.7.2.8

No basic_stringbuf, basic_stringstream

Although the ISO standard i/ostringstream-classes are provided, (), for compatibility with older implementations the pre-ISO i/ostrstream () interface is also provided, with these caveats:
• strstream is considered to be deprecated
• strstream is limited to char
• with ostringstream you don’t have to take care of terminating the string or freeing its memory
• istringstream can be re-filled (clear(); str(input);)
You can then use output-stringstreams like this:
#ifdef HAVE_SSTREAM
# include 
#else
# include 
#endif
#ifdef HAVE_SSTREAM
std::ostringstream oss;
#else
std::ostrstream oss;
#endif
oss << "Name=" << m_name << ", number=" << m_number << std::endl;
...
#ifndef HAVE_SSTREAM
oss << std::ends; // terminate the char*-string
#endif
// str() returns char* for ostrstream and a string for ostringstream
// this also causes ostrstream to think that the buffer’s memory
// is yours
m_label.set_text(oss.str());
#ifndef HAVE_SSTREAM
// let the ostrstream take care of freeing the memory
oss.freeze(false);
#endif

Input-stringstreams can be used similarly:

The GNU C++ Library Manual

371 / 399

std::string input;
...
#ifdef HAVE_SSTREAM
std::istringstream iss(input);
#else
std::istrstream iss(input.c_str());
#endif
int i;
iss >> i;

One (the only?) restriction is that an istrstream cannot be re-filled:
std::istringstream iss(numerator);
iss >> m_num;
// this is not possible with istrstream
iss.clear();
iss.str(denominator);
iss >> m_den;

If you don’t care about speed, you can put these conversions in a template-function:
template 
void fromString(const string& input, X& any)
{
#ifdef HAVE_SSTREAM
std::istringstream iss(input);
#else
std::istrstream iss(input.c_str());
#endif
X temp;
iss >> temp;
if (iss.fail())
throw runtime_error(..)
any = temp;
}

Another example of using stringstreams is in this howto.
There is additional information in the libstdc++-v2 info files, in particular “info iostream”.
B.7.2.9

Little or no wide character support

Classes wstring and char_traits are not supported.
B.7.2.10

No templatized iostreams

Classes wfilebuf and wstringstream are not supported.
B.7.2.11

Thread safety issues

Earlier GCC releases had a somewhat different approach to threading configuration and proper compilation. Before GCC 3.0,
configuration of the threading model was dictated by compiler command-line options and macros (both of which were somewhat
thread-implementation and port-specific). There were no guarantees related to being able to link code compiled with one set of
options and macro setting with another set.
For GCC 3.0, configuration of the threading model used with libraries and user-code is performed when GCC is configured
and built using the --enable-threads and --disable-threads options. The ABI is stable for symbol name-mangling and limited
functional compatibility exists between code compiled under different threading models.

The GNU C++ Library Manual

372 / 399

The libstdc++ library has been designed so that it can be used in multithreaded applications (with libstdc++-v2 this was only
true of the STL parts.) The first problem is finding a fast method of implementation portable to all platforms. Due to historical
reasons, some of the library is written against per-CPU-architecture spinlocks and other parts against the gthr.h abstraction layer
which is provided by gcc. A minor problem that pops up every so often is different interpretations of what "thread-safe" means
for a library (not a general program). We currently use the same definition that SGI uses for their STL subset. However, the
exception for read-only containers only applies to the STL components. This definition is widely-used and something similar
will be used in the next version of the C++ standard library.
Here is a small link farm to threads (no pun) in the mail archives that discuss the threading problem. Each link is to the first
relevant message in the thread; from there you can use "Thread Next" to move down the thread. This farm is in latest-to-oldest
order.
• Our threading expert Loren gives a breakdown of the six situations involving threads for the 3.0 release series.
• This message inspired a recent updating of issues with threading and the SGI STL library. It also contains some example
POSIX-multithreaded STL code.
(A large selection of links to older messages has been removed; many of the messages from 1999 were lost in a disk crash, and
the few people with access to the backup tapes have been too swamped with work to restore them. Many of the points have been
superseded anyhow.)

B.7.3

Third

The third generation GNU C++ library is called libstdc++, or libstdc++-v3.
The subset commonly known as the Standard Template Library (clauses 23 through 25, mostly) is adapted from the final release
of the SGI STL (version 3.3), with extensive changes.
A more formal description of the V3 goals can be found in the official design document.
Portability notes and known implementation limitations are as follows.
B.7.3.1

Pre-ISO headers removed

The pre-ISO C++ headers (,  etc.) are not supported.
For those of you new to ISO C++ (welcome, time travelers!), the ancient pre-ISO headers have new names. The C++ FAQ has a
good explanation in What’s the difference between  and  headers?.
Porting between pre-ISO headers and ISO headers is simple: headers like  can be replaced with  and
a using directive using namespace std; can be put at the global scope. This should be enough to get this code compiling,
assuming the other usage is correct.
B.7.3.2

Extension headers hash_map, hash_set moved to ext or backwards

At this time most of the features of the SGI STL extension have been replaced by standardized libraries. In particular, the
unordered_map and unordered_set containers of TR1 and C++ 2011 are suitable replacements for the non-standard
hash_map and hash_set containers in the SGI STL.
Header files  and  moved to  and , respectively. At the
same time, all types in these files are enclosed in namespace __gnu_cxx. Later versions deprecate these files, and suggest
using TR1’s  and  instead.
The extensions are no longer in the global or std namespaces, instead they are declared in the __gnu_cxx namespace. For
maximum portability, consider defining a namespace alias to use to talk about extensions, e.g.:

The GNU C++ Library Manual

#ifdef __GNUC__
#if __GNUC__ < 3
#include 
namespace extension { using ::hash_map; }; // inherit globals
#else
#include 
#if __GNUC__ == 3 && __GNUC_MINOR__ == 0
namespace extension = std;
// GCC 3.0
#else
namespace extension = ::__gnu_cxx;
// GCC 3.1 and later
#endif
#endif
#else
// ... there are other compilers, right?
namespace extension = std;
#endif
extension::hash_map my_map;

This is a bit cleaner than defining typedefs for all the instantiations you might need.
The following autoconf tests check for working HP/SGI hash containers.
# AC_HEADER_EXT_HASH_MAP
AC_DEFUN([AC_HEADER_EXT_HASH_MAP], [
AC_CACHE_CHECK(for ext/hash_map,
ac_cv_cxx_ext_hash_map,
[AC_LANG_SAVE
AC_LANG_CPLUSPLUS
ac_save_CXXFLAGS="$CXXFLAGS"
CXXFLAGS="$CXXFLAGS -Werror"
AC_TRY_COMPILE([#include ], [using __gnu_cxx::hash_map;],
ac_cv_cxx_ext_hash_map=yes, ac_cv_cxx_ext_hash_map=no)
CXXFLAGS="$ac_save_CXXFLAGS"
AC_LANG_RESTORE
])
if test "$ac_cv_cxx_ext_hash_map" = yes; then
AC_DEFINE(HAVE_EXT_HASH_MAP,,[Define if ext/hash_map is present. ])
fi
])
# AC_HEADER_EXT_HASH_SET
AC_DEFUN([AC_HEADER_EXT_HASH_SET], [
AC_CACHE_CHECK(for ext/hash_set,
ac_cv_cxx_ext_hash_set,
[AC_LANG_SAVE
AC_LANG_CPLUSPLUS
ac_save_CXXFLAGS="$CXXFLAGS"
CXXFLAGS="$CXXFLAGS -Werror"
AC_TRY_COMPILE([#include ], [using __gnu_cxx::hash_set;],
ac_cv_cxx_ext_hash_set=yes, ac_cv_cxx_ext_hash_set=no)
CXXFLAGS="$ac_save_CXXFLAGS"
AC_LANG_RESTORE
])
if test "$ac_cv_cxx_ext_hash_set" = yes; then
AC_DEFINE(HAVE_EXT_HASH_SET,,[Define if ext/hash_set is present. ])
fi
])

373 / 399

The GNU C++ Library Manual

B.7.3.3

374 / 399

No ios::nocreate/ios::noreplace.

Historically these flags were used with iostreams to control whether new files are created or not when opening a file stream,
similar to the O_CREAT and O_EXCL flags for the open(2) system call. Because iostream modes correspond to fopen(3)
modes these flags are not supported. For input streams a new file will not be created anyway, so ios::nocreate is not needed.
For output streams, a new file will be created if it does not exist, which is consistent with the behaviour of fopen.
When one of these flags is needed a possible alternative is to attempt to open the file using std::ifstream first to determine
whether the file already exists or not. This may not be reliable however, because whether the file exists or not could change
between opening the std::istream and re-opening with an output stream. If you need to check for existence and open a file as a
single operation then you will need to use OS-specific facilities outside the C++ standard library, such as open(2).
B.7.3.4

No stream::attach(int fd)

Phil Edwards writes: It was considered and rejected for the ISO standard. Not all environments use file descriptors. Of those that
do, not all of them use integers to represent them.
For a portable solution (among systems which use file descriptors), you need to implement a subclass of std::streambuf
(or std::basic_streambuf<..>) which opens a file given a descriptor, and then pass an instance of this to the streamconstructor.
An extension is available that implements this.  contains a derived class called __gnu_cxx::
stdio_filebuf. This class can be constructed from a C FILE* or a file descriptor, and provides the fd() function.
For another example of this, refer to fdstream example by Nicolai Josuttis.
B.7.3.5

Support for C++98 dialect.

Check for complete library coverage of the C++1998/2003 standard.
# AC_HEADER_STDCXX_98
AC_DEFUN([AC_HEADER_STDCXX_98], [
AC_CACHE_CHECK(for ISO C++ 98 include files,
ac_cv_cxx_stdcxx_98,
[AC_LANG_SAVE
AC_LANG_CPLUSPLUS
AC_TRY_COMPILE([
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include
#include
#include
#include
#include
#include
#include









The GNU C++ Library Manual

#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
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