Datalog Instructions
datalog_instructions
User Manual:
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1. To get started, install the DLV system on your computer.
2. Read the DLV tutorial. There are some notions that will not be easy to understand
at first. In particular, try and understand the following most important subparts:
– The Family Tree Example: Predicates, Variables, and Recursion
– DLV as a Deductive Database System: Comparison Operators
3. Download!and!extract!the!datalog_assignment.zip!file.!In!the!extracted!zip!file,!you!will!
find!2!dlv!files:!family.dlv!and!publication.dlv.!
4. You!must!answer!the!following!problems!in!the!dlv!files!by!using!facts! that! have!been!
given.!Make!sure!you!answer!them!using!the!correct!rule!name.!
5. You!are!not!able!to!add!more!facts!other!than!the!ones!that!have!been!given.!However,!
you!can!add!additional!rules!to!support!your!answer.!
6. You! can! test! your! answer! using! the! Python! script! dlvExecutor.py;! execute! it! using!
Python2.7.!For!example:!python2.7!dlvExecutor.py!
7. After!your!answers!are!ready!(family.dlv!and!publication.dlv),!you!can!submit!them!all!at!
once!using!submit.py;!execute!the!script!using!Python!2.7!as!well.!
8. After!submission,!you!can!check!the!grading!results!in!the!Coursera!web!submission!page.!
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1. descendant:!descendant(X,Y)!holds!if!X!is!a!descendant!of!Y!!
2. sibling:!sibling(X!,Y)!holds!if!X!and!Y!are!siblings.!Hint:!X!and!Y!share!a!parent!P.!!
3. Write! the! following! integrity! constraints! (ICs)! as! “soft! constraints”! in! denial' form,! i.e.,!
write!rules!that!yield!variable!bindings!that!serve!as!“constraint!violation!witnesses”:!
a. icv_person_has_parent:!!Every'person'must'have'a'parent.!Hint:!Look!at!the!IC-rules!
in!the!course!handouts.!!
b. icv_person_has_father_mother:!Every'person'has'a'father'and'a'mother.'Hint:!Same!
idea!as!in!the!Warm-Up.!First,!write!a!rule!that!yields!the!people!for!which!the!IC!is!
satisfied.!Then!write!another!rule!that!reports!as!an!IC-violation!those!people!who!are!
not'in!the!answer!to!that!first!query.!!
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Consider! “dirty”! dataset! store! publication! data! in! this! following! relation.! The! IC-checking!
capabilities!of!a!database!provide!a!powerful!way!to!detect!inconsistencies.!!
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This! relational! dataset! has! been! transformed! into! Datalog! format,! which! you! can! find! in!
publication.dlv.!
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1. Define!the!following!ICs!in!denial'form'in!Datalog!syntax.!You!can!assume!that!the!table!
is!available!as!a!Datalog!predicate!of!the!form!publication(I,!A,!Y,!T,!J,!V,!N,!F,!L,!P).!Recall!
that!in!Datalog,!arbitrary!(capitalized)! names! can!be!chosen!as!variables! since! it!is!the!
argument!position'that!determines!which!attribute/column!is!meant.!
a. icv_pid_key:!The!publication!identifier!Pid!is!a!key,!i.e.,!if!a!row!agrees!with!another!
row!on!the!key!attribute!Pid,!then!it!also!agrees!on!all!other!attributes!(i.e.,!the!“two”!
rows!are!in!fact!one!and!the!same).!As!usual,!your!rule!should!return!the!IC-violations.!
!
b. icv_journal_publisher:! Every! journal! has! a! single! publisher.! Like! (FD-1),! this! is! a!
functional'dependency.!It!is!sometimes!written!as!Journal!→!Publisher.!!
c. ncv_firstpage_lastpage:! The! last! page! Lp! cannot! be! smaller! than! the! first! page! Fp.!
Note:!This!numerical!constraint!can!be!evaluated!independently!on!each!row.!
2. Now! consider! that! an! additional! table! cites(P1,! P2)! is! given,! which! records! pairs! of!
publication!P1,!P2,!where!P1!is!citing!P2.!Define!the!following!IC!in!denial!form:!!
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a. icv_cited_publication:!Every! cited!publication! in!CITES! also!occurs! in!PUBLICATION.!
This! is! an! inclusion' dependency' and! is! usually! written! in! the! form:! CITES[Pid2]! ⊆!
PUBLICATION[Pid].!!
b. ncv_p1_greater_p2:!If! P1! cites!P2,! then! P2’s!year! of! publication! cannot! be! greater!
than!P1’s!year!of!publication.!
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