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International Symposium on Automated Technology for Verification and Analysis

ATVA 2016: Automated Technology for Verification and Analysis pp 130–137Cite as

MoChiBA: Probabilistic LTL Model Checking Using Limit-Deterministic Büchi Automata

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9938))

Abstract

The limiting factor for quantitative analysis of Markov decision processes (MDP) against specifications given in linear temporal logic (LTL) is the size of the generated product. As recently shown, a special subclass of limit-deterministic Büchi automata (LDBA) can replace deterministic Rabin automata in quantitative probabilistic model checking algorithms. We present an extension of PRISM for LTL model checking of MDP using LDBA. While existing algorithms can be used only with minimal changes, the new approach takes advantage of the special structure and the smaller size of the obtained LDBA to speed up the model checking. We demonstrate the speed up experimentally by a comparison with other approaches.

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Acknowledgements

This work is partially funded by the DFG Research Training Group “PUMA: Programm- und Modell-Analyse” (GRK 1480) and by the Czech Science Foundation, grant No. 15-17564S.

The authors want to thank Ernst Moritz Hahn and Andrea Turrini for providing a private version of IscasMC to compare to and for assistance in using it.

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Authors and Affiliations

  1. Technische Universität München, Munich, Germany

    Salomon Sickert & Jan Křetínský

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  1. Salomon Sickert
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  2. Jan Křetínský
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Correspondence to Salomon Sickert .

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Editors and Affiliations

  1. AIST , Osaka, Japan

    Cyrille Artho

  2. Inria Rennes , Rennes, France

    Axel Legay

  3. Bar Ilan University , Ramat Gan, Israel

    Doron Peled

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Sickert, S., Křetínský, J. (2016). MoChiBA: Probabilistic LTL Model Checking Using Limit-Deterministic Büchi Automata. In: Artho, C., Legay, A., Peled, D. (eds) Automated Technology for Verification and Analysis. ATVA 2016. Lecture Notes in Computer Science(), vol 9938. Springer, Cham. https://doi.org/10.1007/978-3-319-46520-3_9

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  • DOI: https://doi.org/10.1007/978-3-319-46520-3_9

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  • Online ISBN: 978-3-319-46520-3

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