Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-34281-3_27
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dc.titleAn analytical and experimental comparison of CSP extensions and tools
dc.contributor.authorShi, L.
dc.contributor.authorLiu, Y.
dc.contributor.authorSun, J.
dc.contributor.authorDong, J.S.
dc.contributor.authorCarvalho, G.
dc.date.accessioned2013-07-23T09:27:07Z
dc.date.available2013-07-23T09:27:07Z
dc.date.issued2012
dc.identifier.citationShi, L.,Liu, Y.,Sun, J.,Dong, J.S.,Carvalho, G. (2012). An analytical and experimental comparison of CSP extensions and tools. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7635 LNCS : 381-397. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-34281-3_27" target="_blank">https://doi.org/10.1007/978-3-642-34281-3_27</a>
dc.identifier.isbn9783642342806
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/43178
dc.description.abstractCommunicating Sequential Processes (CSP) has been widely applied to modeling and analyzing concurrent systems. There have been considerable efforts on enhancing CSP by taking data and other system aspects into account. For instance, CSPM combines CSP with a functional programming language whereas CSP# integrates high-level CSP-like process operators with low-level procedure code. Little work has been done to systematically compare these CSP extensions, which may have subtle and substantial differences. In this paper, we compare CSPM and CSP# not only on their syntax, but also operational semantics as well as their supporting tools such as FDR, ProB, and PAT. We conduct extensive experiments to compare the performance of these tools in different settings. Our comparison can be used to guide users to choose the appropriate CSP extension and verification tool based on the system characteristics. © 2012 Springer-Verlag.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-34281-3_27
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.contributor.departmentTEMASEK LABORATORIES
dc.description.doi10.1007/978-3-642-34281-3_27
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume7635 LNCS
dc.description.page381-397
dc.identifier.isiutNOT_IN_WOS
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