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A Progress Measure for Explicit-State Probabilistic Model-Checkers

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Automata, Languages and Programming (ICALP 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6756))

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Abstract

Verification of the source code of a probabilistic system by means of an explicit-state model-checker is challenging. In most cases, the probabilistic model-checker will run out of memory due to the infamous state space explosion problem. As far as we know, we are the first to introduce the notion of a progress measure for such a model-checker. The progress measure returns a number in the interval [0, 1]. This number captures the amount of progress the model-checker has made towards verifying a particular linear-time property. The larger the number, the more progress the model-checker has made. We prove that the progress measure provides a lower bound of the measure of the set of execution paths that satisfy the property. We also show how to compute the progress measure for checking a particular class of linear-time properties, namely invariants.

This research is supported by NSERC.

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References

  1. Baier, C., Katoen, J.P.: Principles of Model Checking. The MIT Press, Cambridge (2008)

    MATH  Google Scholar 

  2. Billingsley, P.: Probability and Measure. John Wiley & Sons, Chichester (1995)

    MATH  Google Scholar 

  3. Katoen, J.P., Zapreev, I.S., Hahn, E.M., Hermanns, H., Jansen, D.N.: The ins and outs of the probabilistic model checker MRMC. Performance Evaluation 68(2), 90–104 (2011)

    Article  Google Scholar 

  4. Kemeny, J.G., Snell, J.L., Knapp, A.W.: Denumerable Markov Chains. Van Nostrand, New York (1966)

    MATH  Google Scholar 

  5. Kwiatkowska, M., Norman, G., Parker, D.: Probabilistic symbolic model checking with PRISM: A hybrid approach. International Journal on Software Tools for Technology Transfer 6(2), 128–142 (2004)

    Article  MATH  Google Scholar 

  6. Pavese, E., Braberman, V., Uchitel, S.: My model checker died!: how well did it do? In: Proceedings of the 2010 ICSE Workshop on Quantitative Stochastic Models in the Verification and Design of Software Systems, pp. 33–40. ACM, New York (2010)

    Google Scholar 

  7. Della Penna, G., Intrigila, B., Melatti, I., Tronci, E., Venturini Zilli, M.: Finite horizon analysis of Markov chains with the Murϕ verifier. International Journal on Software Tools for Technology 8(4/5), 397–409 (2006)

    Article  MATH  Google Scholar 

  8. Vardi, M.Y.: Automatic verification of probabilistic finite-state programs. In: Proceedings of the 26th IEEE Symposium on Foundations of Computer Science, pp. 327–338. IEEE, Los Alamitos (1985)

    Google Scholar 

  9. Visser, W., Havelund, K., Brat, G., Park, S., Lerda, F.: Model checking programs. Automated Software Engineering 10(2), 203–232 (2003)

    Article  Google Scholar 

  10. Zhang, X.: Measuring Progress of Model Checking Randomized Algorithms. Master’s thesis. York University, Toronto (2010)

    Google Scholar 

  11. Zhang, X., Breugel, F.v.: Measuring progress of Java PathFinder model-checking randomized sequential code. In: Preliminary Proceedings of the 6th Workshop on Quantitative Aspects of Programming Languages, 4 pages (2008)

    Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Zhang, X., van Breugel, F. (2011). A Progress Measure for Explicit-State Probabilistic Model-Checkers. In: Aceto, L., Henzinger, M., Sgall, J. (eds) Automata, Languages and Programming. ICALP 2011. Lecture Notes in Computer Science, vol 6756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22012-8_22

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  • DOI: https://doi.org/10.1007/978-3-642-22012-8_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22011-1

  • Online ISBN: 978-3-642-22012-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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