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Model checking of continuous-time Markov Chains against timed automata specifications

机译:根据定时自动机规范对连续时间马尔可夫链进行模型检查

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摘要

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 approximated by the solution of a system of partial differential equations. For single-clock DTA, this integral equation system can be transformed into a system of linear equations where the coefficients are solutions of ordinary differential equations. As the coefficients are in fact transient probabilities in CTMCs, this result implies that standard algorithms for CTMC analysis suffice to verify single-clock DTA specifications.
机译:我们研究了针对线性实时规范的有限连续时间马尔可夫链(CTMC)C的验证,线性实时规范作为具有确定或穆勒接受条件的确定性定时自动机(DTA)A给出。我们要解决的中心问题是:A接受C的路径集的概率是多少,即C满足A的可能性是多少?结果表明,在有限接受准则下,这等于有限分段确定性马尔可夫过程(PDP)中的可达性概率,而对于穆勒接受准则,它与此类PDP中终端强连接组件的可达性概率相符。显示的定性验证相当于对PDP的图形分析。然后将我们PDP中的可到达性概率表征为第二类型Volterra积分方程组的最小解,并显示为通过偏微分方程组的解近似。对于单时钟DTA,可以将该积分方程组转换为线性方程组,其中系数是常微分方程的解。由于系数实际上是CTMC中的瞬态概率,因此该结果表明CTMC分析的标准算法足以验证单时钟DTA规范。

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