Bounded Model Checking for GSMP Models of Stochastic Real-Time Systems

  • Rajeev Alur
  • Mikhail Bernadsky
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3927)


Model checking is a popular algorithmic verification technique for checking temporal requirements of mathematical models of systems. In this paper, we consider the problem of verifying bounded reachability properties of stochastic real-time systems modeled as generalized semi-Markov processes (GSMP). While GSMPs is a rich model for stochastic systems widely used in performance evaluation, existing model checking algorithms are applicable only to subclasses such as discrete-time or continuous-time Markov chains. The main contribution of the paper is an algorithm to compute the probability that a given GSMP satisfies a property of the form “can the system reach a target before time T within k discrete events, while staying within a set of safe states”. For this, we show that the probability density function for the remaining firing times of different events in a GSMP after k discrete events can be effectively partitioned into finitely many regions and represented by exponentials and polynomials. We report on illustrative examples and their analysis using our techniques.


Model Check Mass Point Destination Location Discrete Event System Symbolic Model Check 
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© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Rajeev Alur
    • 1
  • Mikhail Bernadsky
    • 1
  1. 1.Department of Computer and Information ScienceUniversity of PennsylvaniaUSA

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