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Don’t Know in Probabilistic Systems

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Model Checking Software (SPIN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3925))

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Abstract

In this paper the abstraction-refinement paradigm based on 3-valued logics is extended to the setting of probabilistic systems. We define a notion of abstraction for Markov chains. To be able to relate the behavior of abstract and concrete systems, we equip the notion of abstraction with the concept of simulation. Furthermore, we present model checking for abstract probabilistic systems (abstract Markov chains) with respect to specifications in probabilistic temporal logics, interpreted over a 3-valued domain. More specifically, we introduce a 3-valued version of probabilistic computation-tree logic (PCTL) and give a model checking algorithm w.r.t. abstract Markov chains.

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References

  1. Baier, C.: On the algorithmic verification of probabilistic systems. Universität Mannheim, Habilitation Thesis (1998)

    Google Scholar 

  2. Chechik, M., Devereux, B., Easterbrook, S., Gurfinkel, A.: Multi-valued symbolic model-checking. ACM Transactions on Software Engineering and Methodology (TOSEM) 12, 371–408 (2003)

    Article  MATH  Google Scholar 

  3. Clarke, E., Grumberg, O., Long, D.: Model Checking and Abstraction. In: Proc. of POPL, January 1992, pp. 342–354. ACM, New York (1992)

    Google Scholar 

  4. Clarke, E.M., Grumberg, O., Peled, D.A.: Model Checking. MIT Press, Cambridge (1999)

    Google Scholar 

  5. Courcoubetis, C., Yannakakis, M.: The complexity of probabilistic verification. Journal of the ACM 42(4), 857–907 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  6. D’Argenio, P., Jeannet, B., Jensen, H., Larsen, K.: Reduction and refinement strategies for probabilistic analysis. In: Hermanns, H., Segala, R. (eds.) PROBMIV 2002, PAPM-PROBMIV 2002, and PAPM 2002. LNCS, vol. 2399, pp. 57–76. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  7. de Alfaro, L.: Formal Verification of Probabilistic Systems. PhD thesis, Stanford University, Technical report STAN-CS-TR-98-1601 (1997)

    Google Scholar 

  8. Godefroid, P., Jagadeesan, R.: On the expressiveness of 3-valued models. In: Zuck, L.D., Attie, P.C., Cortesi, A., Mukhopadhyay, S. (eds.) VMCAI 2003. LNCS, vol. 2575, pp. 206–222. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  9. Grumberg, O., Lange, M., Leucker, M., Shoham, S.: Don’t know in the μ-calculus. In: Cousot, R. (ed.) VMCAI 2005. LNCS, vol. 3385, pp. 233–249. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  10. Hansson, H., Jonsson, B.: A logic for reasoning about time and reliability. Formal Aspects of Computing 6, 512–535 (1994)

    Article  MATH  Google Scholar 

  11. Huth, M.: On finite-state approximants for probabilistic computation tree logic. Theoretical Computer Science (to appear)

    Google Scholar 

  12. Huth, M.: An abstraction framework for mixed non-deterministic and probabilistic systems. In: Validation of Stochastic Systems, pp. 419–444 (2004)

    Google Scholar 

  13. Huth, M., Jagadeesan, R., Schmidt, D.: Modal transition systems: A foundation for three-valued program analysis. In: Sands, D. (ed.) ESOP 2001. LNCS, vol. 2028, pp. 155–169. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  14. Huth, M.: Abstraction and probabilities for hybrid logics. In: Qualitative Aspects of Programming Languages (2004)

    Google Scholar 

  15. Jonsson, B., Larsen, K.: Specification and refinement of probabilistic processes. In: Proc. 6th IEEE Int. Symp. on Logic in Computer Science (1991)

    Google Scholar 

  16. Konikowska, B., Penczek, W.: Model checking for multi-valued computation tree logics. In: Beyond two: theory and applications of multiple-valued logic, pp. 193–210. Physica-Verlag, Heidelberg (2003)

    Chapter  Google Scholar 

  17. Konikowska, B., Penczek, W.: On designated values in multi-valued CTL ∗  model checking. Fundamenta Informaticae 60(1–4), 221–224 (2004)

    MathSciNet  MATH  Google Scholar 

  18. Shoham, S., Grumberg, O.: A game-based framework for CTL counterexamplesand 3-valued abstraction-refinemnet. In: Hunt Jr., W.A., Somenzi, F. (eds.) CAV 2003. LNCS, vol. 2725, pp. 275–287. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  19. van Glabbeek, R., Smolka, S., Steffen, B., Tofts, C.: Reactive, generative, and stratified models of probabilistic processes. In: Logic in Computer Science, pp. 130–141 (1990)

    Google Scholar 

  20. Yi, W.: Reasoning about uncertain information compositionally. In: Langmaack, H., de Roever, W.-P., Vytopil, J. (eds.) FTRTFT 1994 and ProCoS 1994. LNCS, vol. 863, Springer, Heidelberg (1994)

    Chapter  Google Scholar 

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Fecher, H., Leucker, M., Wolf, V. (2006). Don’t Know in Probabilistic Systems. In: Valmari, A. (eds) Model Checking Software. SPIN 2006. Lecture Notes in Computer Science, vol 3925. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11691617_5

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  • DOI: https://doi.org/10.1007/11691617_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33102-5

  • Online ISBN: 978-3-540-33103-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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