Counterexample Generation in Probabilistic Model Checking

Tingting Han, Joost P. Katoen, B. Damman

    Research output: Contribution to journalArticleAcademicpeer-review

    76 Citations (Scopus)
    69 Downloads (Pure)

    Abstract

    Providing evidence for the refutation of a property is an essential, if not the most important, feature of model checking. This paper considers algorithms for counterexample generation for probabilistic CTL formulae in discrete-time Markov chains. Finding the strongest evidence (i.e., the most probable path) violating a (bounded) until-formula is shown to be reducible to a single-source (hop-constrained) shortest path problem. Counterexamples of smallest size that deviate most from the required probability bound can be obtained by applying (small amendments to) k-shortest (hop-constrained) paths algorithms. These results can be extended to Markov chains with rewards, to LTL model checking, and are useful for Markov decision processes. Experimental results show that typically the size of a counterexample is excessive. To obtain much more compact representations, we present a simple algorithm to generate (minimal) regular expressions that can act as counterexamples. The feasibility of our approach is illustrated by means of two communication protocols: leader election in an anonymous ring network and the Crowds protocol.
    Original languageUndefined
    Article number10.1109/TSE.2009.5
    Pages (from-to)241-257
    Number of pages17
    JournalIEEE transactions on software engineering
    Volume35
    Issue number2
    DOIs
    Publication statusPublished - 2009

    Keywords

    • FMT-PM: PROBABILISTIC METHODS
    • FMT-MC: MODEL CHECKING
    • IR-68146
    • METIS-264046
    • EWI-16105

    Cite this