PVeStA: A Parallel Statistical Model Checking and Quantitative Analysis Tool

Musab AlTurki, José Meseguer

Research output: Chapter in Book/Report/Conference proceedingChapter

64 Scopus citations

Abstract

Statistical 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.
Original languageEnglish (US)
Title of host publicationAlgebra and Coalgebra in Computer Science
PublisherSpringer Nature
Pages386-392
Number of pages7
ISBN (Print)9783642229435
DOIs
StatePublished - 2011
Externally publishedYes

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