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dc.contributor.authorJi, K
dc.contributor.authorLiu, Y
dc.contributor.authorLin, SW
dc.contributor.authorSun, J
dc.contributor.authorDong, JS
dc.contributor.authorNguyen, TK
dc.date.accessioned2017-10-24T04:00:38Z
dc.date.available2017-10-24T04:00:38Z
dc.date.issued2013
dc.identifier.issn0302-9743
dc.identifier.doi10.1007/978-3-319-02444-8_38
dc.identifier.urihttp://hdl.handle.net/10072/172898
dc.description.abstractThis paper presents CELL, a comprehensive and extensible framework for compositional verification of concurrent and real-time systems based on commonly used semantic models. For each semantic model, CELL offers three libraries, i.e., compositional verification paradigms, learning algorithms and model checking methods to support various state-of-the-art compositional verification approaches. With well-defined APIs, the framework could be applied to build customized model checkers. In addition, each library could be used independently for verification and program analysis purposes. We have built three model checkers with CELL. The experimental results show that the performance of these model checkers can offer similar or often better performance compared to the state-of-the-art verification tools.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherSpringer
dc.relation.ispartofpagefrom474
dc.relation.ispartofpageto477
dc.relation.ispartofjournalLecture Notes in Computer Science
dc.relation.ispartofvolume8172 LNAI
dc.subject.fieldofresearchSoftware engineering not elsewhere classified
dc.subject.fieldofresearchcode461299
dc.titleCELL: A compositional verification framework
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.hasfulltextNo Full Text
gro.griffith.authorDong, Jin-Song


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