Approximative Symbolic Model Checking of Continuous-Time Markov Chains

Extended Abstract
  • Christel Baier
  • Joost-Pieter Katoen
  • Holger Hermanns
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1664)

Abstract

This paper presents a symbolic model checking algorithm for continuous-time Markov chains for an extension of the continuous stochastic logic CSL of Aziz et al [1]. The considered logic contains a time-bounded until-operator and a novel operator to express steadystate probabilities. We show that the model checking problem for this logic reduces to a system of linear equations (for unbounded until and the steady state-operator) and a Volterra integral equation system for timebounded until. We propose a symbolic approximate method for solving the integrals using MTDDs (multi-terminal decision diagrams), a generalisation of MTBDDs. These new structures are suitable for numerical integration using quadrature formulas based on equally-spaced abscissas, like trapezoidal, Simpson and Romberg integration schemes.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Christel Baier
    • 1
  • Joost-Pieter Katoen
    • 2
    • 3
  • Holger Hermanns
    • 3
  1. 1.Lehrstuhl für Praktische Informatik IIUniversity of MannheimMannheimGermany
  2. 2.Lehrstuhl für Informatik 7University of Erlangen-NürnbergErlangenGermany
  3. 3.Systems Validation CentreUniversity of TwenteAE EnschedeThe Netherlands

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