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PVeStA: A Parallel Statistical Model Checking and Quantitative Analysis Tool

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 6859)

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.

Keywords

  • Model Check
  • Temporal Logic
  • Statistical Model Check
  • Temporal Logic Formula
  • Path Formula

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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AlTurki, M., Meseguer, J. (2011). PVeStA: A Parallel Statistical Model Checking and Quantitative Analysis Tool. In: Corradini, A., Klin, B., Cîrstea, C. (eds) Algebra and Coalgebra in Computer Science. CALCO 2011. Lecture Notes in Computer Science, vol 6859. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22944-2_28

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  • DOI: https://doi.org/10.1007/978-3-642-22944-2_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22943-5

  • Online ISBN: 978-3-642-22944-2

  • eBook Packages: Computer ScienceComputer Science (R0)