PRISM: A tool for automatic verification of probabilistic systems

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PRISM: A tool for automatic verification of probabilistic systems (2006)

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by Andrew Hinton , Marta Kwiatkowska , Gethin Norman , David Parker

Venue:	Proc. 12th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS’06), volume 3920 of LNCS
Citations:	282 - 33 self

BibTeX

@INPROCEEDINGS{Hinton06prism:a,
    author = {Andrew Hinton and Marta Kwiatkowska and Gethin Norman and David Parker},
    title = {PRISM: A tool for automatic verification of probabilistic systems},
    booktitle = {Proc. 12th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS’06), volume 3920 of LNCS},
    year = {2006},
    pages = {441--444},
    publisher = {Springer}
}

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Abstract

Abstract. Probabilistic model checking is an automatic formal verification technique for analysing quantitative properties of systems which exhibit stochastic behaviour. PRISM is a probabilistic model checking tool which has already been successfully deployed in a wide range of application domains, from real-time communication protocols to biological signalling pathways. The tool has recently undergone a significant amount of development. Major additions include facilities to manually explore models, Monte-Carlo discrete-event simulation techniques for approximate model analysis (including support for distributed simulation) and the ability to compute cost- and reward-based measures, e.g. “the expected energy consumption of the system before the first failure occurs”. This paper presents an overview of all the main features of PRISM. More information can be found on the website: www.cs.bham.ac.uk/˜dxp/prism. 1

Keyphrases

automatic verification probabilistic system distributed simulation quantitative property automatic formal verification technique application domain probabilistic model first failure approximate model analysis real-time communication protocol major addition significant amount uk dxp prism wide range probabilistic model checking biological signalling pathway monte-carlo discrete-event simulation technique expected energy consumption reward-based measure stochastic behaviour main feature

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