Model-checking algorithms for continuous-time Markov chains

doi:10.1109/TSE.2003.1205180

Model-checking algorithms for continuous-time Markov chains

2003-06-01

502

OA

AI

C

Christel Baier

B

Boudewijn R. Haverkort

DOI：10.1109/TSE.2003.1205180

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Abstract

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Continuous-time Markov chains (CTMCs) have been widely used to determine system performance and dependability characteristics. Their analysis most often concerns the computation of steady-state and transient-state probabilities. This paper introduces a branching temporal logic for expressing real-time probabilistic properties on CTMCs and presents approximate model checking algorithms for this logic. The logic, an extension of the continuous stochastic logic CSL of Aziz et al., Contains a time-bounded until operator to express probabilistic timing properties over paths as well as an operator to express steady-state 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 time-bounded until). We then show that the problem of model-checking time-bounded until properties can be reduced to the problem of computing transient state probabilities for CTMCs. This allow's the verification of probabilistic timing properties by efficient techniques for transient analysis for CTMCs such as uniformization. Finally, we show that a variant of lumping equivalence (bisimulation), a well-known notion for aggregating CTMCs, preserves the validity of aft formulas in the logic.

Keywords:

continuous-time Markov chain

lumping

model checking

temporal logic

steady-state analysis

transient analysis

uniformization

Model-checking algorithms for continuous-time Markov chains

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