Counterexample Generation for Discrete-Time Markov Chains Using Bounded Model Checking

  • Ralf Wimmer
  • Bettina Braitling
  • Bernd Becker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5403)


Since its introduction in 1999, bounded model checking has gained industrial relevance for detecting errors in digital and hybrid systems. One of the main reasons for this is that it always provides a counterexample when an erroneous execution trace is found. Such a counterexample can guide the designer while debugging the system.

In this paper we are investigating how bounded model checking can be applied to generate counterexamples for a different kind of model—namely discrete-time Markov chains. Since in this case counterexamples in general do not consist of a single path to a safety-critical state, but of a potentially large set of paths, novel optimization techniques like loop-detection are applied not only to speed-up the counterexample computation, but also to reduce the size of the counterexamples significantly. We report on some experiments which demonstrate the practical applicability of our method.


Model Check Conjunctive Normal Form Binary Decision Diagram Kripke Structure Satisfying Assignment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ralf Wimmer
    • 1
  • Bettina Braitling
    • 1
  • Bernd Becker
    • 1
  1. 1.Chair of Computer ArchitectureAlbert-Ludwigs-University Freiburg im BreisgauGermany

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