Article

PVESTA: a parallel statistical model checking and quantitative analysis tool

Authors:

Musab AlTurki,

José MeseguerAuthors Info & Claims

CALCO'11: Proceedings of the 4th international conference on Algebra and coalgebra in computer science

Pages 386 - 392

Published: 30 August 2011 Publication History

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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.

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Galpin VGeorgoulas ALoreti MVandin AJohansson BJain S(2018)Statistical analysis of CARMA modelsProceedings of the 2018 Winter Simulation Conference10.5555/3320516.3320573(395-409)Online publication date: 9-Dec-2018
https://dl.acm.org/doi/10.5555/3320516.3320573
Alturki MKanovich MBan Kirigin TNigam VScedrov ATalcott CLie DMannan MRashid ATippenhaeur N(2018)Statistical Model Checking of Distance Fraud Attacks on the Hancke-Kuhn Family of ProtocolsProceedings of the 2018 Workshop on Cyber-Physical Systems Security and PrivaCy10.1145/3264888.3264895(60-71)Online publication date: 15-Oct-2018
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CALCO'11: Proceedings of the 4th international conference on Algebra and coalgebra in computer science

August 2011

420 pages

ISBN:9783642229435

Editors:
Andrea Corradini
Università di Pisa, Dipartimento di Informatica, Pisa, Italy
,
Bartek Klin
University of Warsaw, Faculty of Mathematics, Informatics, and Mechanics, Warszawa, Poland
,
Corina Cîrstea
University of Southampton, School of Electronics and Computer Science, Southampton, UK

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Springer-Verlag

Berlin, Heidelberg

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Published: 30 August 2011

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Galpin VGeorgoulas ALoreti MVandin AJohansson BJain S(2018)Statistical analysis of CARMA modelsProceedings of the 2018 Winter Simulation Conference10.5555/3320516.3320573(395-409)Online publication date: 9-Dec-2018
https://dl.acm.org/doi/10.5555/3320516.3320573
Alturki MKanovich MBan Kirigin TNigam VScedrov ATalcott CLie DMannan MRashid ATippenhaeur N(2018)Statistical Model Checking of Distance Fraud Attacks on the Hancke-Kuhn Family of ProtocolsProceedings of the 2018 Workshop on Cyber-Physical Systems Security and PrivaCy10.1145/3264888.3264895(60-71)Online publication date: 15-Oct-2018
https://dl.acm.org/doi/10.1145/3264888.3264895
Broccia GMasci PMilazzo PPietriga ELuyten K(2018)Modeling and Analysis of Human Memory Load in Multitasking ScenariosProceedings of the ACM SIGCHI Symposium on Engineering Interactive Computing Systems10.1145/3220134.3220140(1-7)Online publication date: 19-Jun-2018
https://dl.acm.org/doi/10.1145/3220134.3220140
Agha GPalmskog K(2018)A Survey of Statistical Model CheckingACM Transactions on Modeling and Computer Simulation10.1145/315866828:1(1-39)Online publication date: 31-Jan-2018
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