Goal-directed Weakening of Abstract Interpretation Results

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dc.contributor.authorSeo, Sunaeko
dc.contributor.authorYang, Hongseokko
dc.contributor.authorYi, Kwangkeunko
dc.contributor.authorHan, Taisookko
dc.date.accessioned2010-02-03T05:54:42Z-
dc.date.available2010-02-03T05:54:42Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2007-10-
dc.identifier.citationACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS, v.29, no.10-
dc.identifier.issn0164-0925-
dc.identifier.urihttp://hdl.handle.net/10203/16451-
dc.description.abstractOne proposal for automatic construction of proofs about programs is to combine Hoare logic and abstract interpretation. Constructing proofs is in Hoare logic. Discovering programs' invariants is done by abstract interpreters. One problem of this approach is that abstract interpreters often compute invariants that are not needed for the proof goal. The reason is that the abstract interpreter does not know what the proof goal is, so it simply tries to find as strong invariants as possible. These unnecessary invariants increase the size of the constructed proofs. Unless the proof-construction phase is notified which invariants are not needed, it blindly proves all the computed invariants. In this article, we present a framework for designing algorithms, called abstract-value slicers, that slice out unnecessary invariants from the results of forward abstract interpretation. The framework provides a generic abstract-value slicer that can be instantiated into a slicer for a particular abstract interpretation. Such an instantiated abstract-value slicer works as a postprocessor to an abstract interpretation in the whole proof-construction process, and notifies to the next proof-construction phase which invariants it does not have to prove. Using the framework, we designed an abstract-value slicer for an existing relational analysis and applied it on programs. In this experiment, the slicer identified 62%-81% of the computed invariants as unnecessary, and resulted in 52%-84% reduction in the size of constructed proofs.-
dc.description.sponsorshipS. Seo and T. Han were supported by Korea Ministry of Information and Communication under the Information Technology Research Center support program, supervised by the Institute of Information Technology Assessment (IITA-2005-C1090-0502-0031). H. Yang was supported by EPSRC and the Basic Research Program of the Korea-Science & Engineering Foundation (grant No. R08-2003-000-10370-0). K. Yi was supported by Brain Korea 21 Project of Korea Ministry of Education and Human Resources, by IT Leading R&D Support Project of Korea Ministry of Information and Communication, by Korea Research Foundation grant KRF-2003-041-D00528, and by National Security Research Institute of Korea.en
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherASSOC COMPUTING MACHINERY-
dc.titleGoal-directed Weakening of Abstract Interpretation Results-
dc.typeArticle-
dc.identifier.wosid000250967500010-
dc.identifier.scopusid2-s2.0-36048931056-
dc.type.rimsART-
dc.citation.volume29-
dc.citation.issue10-
dc.citation.publicationnameACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS-
dc.identifier.doi10.1145/1286821.1286830-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorYang, Hongseok-
dc.contributor.localauthorHan, Taisook-
dc.contributor.nonIdAuthorSeo, Sunae-
dc.contributor.nonIdAuthorYi, Kwangkeun-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthoralgorithms-
dc.subject.keywordAuthordesign-
dc.subject.keywordAuthorlanguages-
dc.subject.keywordAuthorverification-
dc.subject.keywordAuthorabstract interpretation-
dc.subject.keywordAuthorbackward analysis-
dc.subject.keywordAuthorhoare logic-
dc.subject.keywordAuthorprogram verification-
dc.subject.keywordAuthorstatic analysis-
dc.subject.keywordPlusDOMAINS-
dc.subject.keywordPlusCONSTRUCTION-
dc.subject.keywordPlusPROOFS-
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