Model Checking of Continuous-Time Markov Chains Against Timed Automata Specifications
Taolue Chen (University of Twente), Tingting Han (RWTH Aachen, University), Joost-Pieter Katoen (RWTH Aachen University), Alexandru Mereacre, (RWTH Aachen University)

TL;DR
This paper presents a method for verifying continuous-time Markov chains against timed automata specifications by translating the problem into reachability analysis in piecewise deterministic Markov processes, enabling the use of standard CTMC algorithms.
Contribution
It introduces a novel approach to model checking CTMCs against timed automata using PDPs and integral equations, extending verification techniques to real-time probabilistic systems.
Findings
Verification reduces to reachability in PDPs.
Qualitative analysis involves graph analysis of PDPs.
Single-clock DTA verification uses standard CTMC algorithms.
Abstract
We study the verification of a finite continuous-time Markov chain (CTMC) C against a linear real-time specification given as a deterministic timed automaton (DTA) A with finite or Muller acceptance conditions. The central question that we address is: what is the probability of the set of paths of C that are accepted by A, i.e., the likelihood that C satisfies A? It is shown that under finite acceptance criteria this equals the reachability probability in a finite piecewise deterministic Markov process (PDP), whereas for Muller acceptance criteria it coincides with the reachability probability of terminal strongly connected components in such a PDP. Qualitative verification is shown to amount to a graph analysis of the PDP. Reachability probabilities in our PDPs are then characterized as the least solution of a system of Volterra integral equations of the second type and are shown to be…
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