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dc.identifier.urihttp://hdl.handle.net/1951/55647
dc.identifier.urihttp://hdl.handle.net/11401/72699
dc.description.sponsorshipThis work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.en_US
dc.formatMonograph
dc.format.mediumElectronic Resourceen_US
dc.language.isoen_US
dc.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dc.typeDissertation
dcterms.abstractMany complex analysis problems can be most clearly and easily specified as logic rules and queries, where rules specify how given facts can be combined to infer new facts, and queries select facts of interest to the analysis problem at hand. However, it has been extremely challenging to obtain efficient implementations from logic rules and understand their time and space complexities, particularly for answering queries of interest without inferring all facts.This dissertation focuses on Datalog---an important class of rules for applications in databases, program analysis, security, semantic web, and many other areas. We describe a systematic method for precisely analyzing the time and space complexities of best known strategies for answering Datalog queries. We also characterize precise relationships among these strategies. Furthermore, we develop new transformations and combine them with existing transformations to drastically optimize the rules and queries for generating efficient implementations. Finally, we show the effectiveness of our analyses and transformations for solving important problems in program analysis, language processing, and semantic web, and for answering graph queries, which have many applications.
dcterms.available2012-05-15T18:07:08Z
dcterms.available2015-04-24T14:53:16Z
dcterms.contributorLiu, Yanhong A.en_US
dcterms.contributorDavid S. Warrenen_US
dcterms.contributorMichael Kiferen_US
dcterms.contributorPatrick Cousot.en_US
dcterms.creatorTekle, Tuncay
dcterms.dateAccepted2012-05-15T18:07:08Z
dcterms.dateAccepted2015-04-24T14:53:16Z
dcterms.dateSubmitted2012-05-15T18:07:08Z
dcterms.dateSubmitted2015-04-24T14:53:16Z
dcterms.descriptionDepartment of Computer Scienceen_US
dcterms.formatMonograph
dcterms.formatApplication/PDFen_US
dcterms.identifierTekle_grad.sunysb_0771E_10394.pdfen_US
dcterms.identifierhttp://hdl.handle.net/1951/55647
dcterms.identifierhttp://hdl.handle.net/11401/72699
dcterms.issued2010-12-01
dcterms.languageen_US
dcterms.provenanceMade available in DSpace on 2012-05-15T18:07:08Z (GMT). No. of bitstreams: 1 Tekle_grad.sunysb_0771E_10394.pdf: 690673 bytes, checksum: 7e540154227c372fb72308f8d871a4e0 (MD5) Previous issue date: 1en
dcterms.provenanceMade available in DSpace on 2015-04-24T14:53:16Z (GMT). No. of bitstreams: 3 Tekle_grad.sunysb_0771E_10394.pdf.jpg: 1894 bytes, checksum: a6009c46e6ec8251b348085684cba80d (MD5) Tekle_grad.sunysb_0771E_10394.pdf.txt: 234928 bytes, checksum: cf9cd9ffe694cd039cfd66ea579ba5ac (MD5) Tekle_grad.sunysb_0771E_10394.pdf: 690673 bytes, checksum: 7e540154227c372fb72308f8d871a4e0 (MD5) Previous issue date: 1en
dcterms.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dcterms.subjectAlgorithms, Databases, Programming Languages, Query-processing
dcterms.subjectComputer Science
dcterms.titleEfficient Datalog Queries with Time and Space Complexity Guarantees
dcterms.typeDissertation


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