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dc.contributor.authorAlTurki, Musab
dc.contributor.authorMeseguer, José
dc.date.accessioned2016-02-28T05:50:43Z
dc.date.available2016-02-28T05:50:43Z
dc.date.issued2011
dc.identifier.citationAlTurki M, Meseguer J (2011) PVeStA: A Parallel Statistical Model Checking and Quantitative Analysis Tool. Lecture Notes in Computer Science: 386–392. Available: http://dx.doi.org/10.1007/978-3-642-22944-2_28.
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.doi10.1007/978-3-642-22944-2_28
dc.identifier.urihttp://hdl.handle.net/10754/599416
dc.description.abstractStatistical model checking is an attractive formal analysis method for probabilistic systems such as, for example, cyber-physical systems which are often probabilistic in nature. This paper is about drastically increasing the scalability of statistical model checking, and making such scalability of analysis available to tools like Maude, where probabilistic systems can be specified at a high level as probabilistic rewrite theories. It presents PVeStA, an extension and parallelization of the VeStA statistical model checking tool [10]. PVeStA supports statistical model checking of probabilistic real-time systems specified as either: (i) discrete or continuous Markov Chains; or (ii) probabilistic rewrite theories in Maude. Furthermore, the properties that it can model check can be expressed in either: (i) PCTL/CSL, or (ii) the QuaTEx quantitative temporal logic. As our experiments show, the performance gains obtained from parallelization can be very high. © 2011 Springer-Verlag.
dc.description.sponsorshipWe thank Koushik Sen, Mahesh Viswanathan, and GulAgha for the original work onVeStA, and Gul Agha and Koushik Sen for theirwork on PMaude andQuaTEx, which provide the basis on whichPVeStAhas been built. This work has been partially supported by NSF grants CNS 08-34709, CNS 07-16638, and CCF 09-05584, King Fahd University of Petroleumand Minerals, and King Abdullah University of Science and Technology.
dc.publisherSpringer Nature
dc.titlePVeStA: A Parallel Statistical Model Checking and Quantitative Analysis Tool
dc.typeBook Chapter
dc.identifier.journalAlgebra and Coalgebra in Computer Science
dc.contributor.institutionUniversity of Illinois at Urbana-Champaign, Urbana, United States


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