Abstract

Boolean-logic Driven Markov Processes (BDMPs) is a graphical language for reliability analysis of dynamic repairable systems. Simulation and trace-based analysis tools for BDMPs exist and have been used to analyze reliability, safety and security aspects of industrially relevant case studies. To enable a model-based analysis of BDMPs, such as probabilistic model checking, formal semantics is indispensable. This paper presents a rigorous semantics to repairable BDMPs using Markov automata (MA), a variant of continuous-time Markov chains (CTMCs) with action transitions. The semantics is modular: an MA is associated with each BDMP element and these are combined to obtain an automaton for the entire BDMP. By ignoring the actions that are used to “glue” the MA of BDMP elements, a CTMC is obtained that is amenable to analysis by e.g., model checking. We report on a prototypical implementation and experimentally show that our semantics corresponds to the BDMP interpretation by the tool Yet Another Monte Carlo Simulation.

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