From probabilistic counterexamples via causality to fault trees

Abstract

Probabilistic Model Checking is an established technique used in the dependability analysis of safety-critical systems. In recent years, several approaches to generate probabilistic counterexamples have been proposed. The interpretation of stochastic counterexamples, however, continues to be problematic since they have to be represented as sets of paths, and the number of paths in this set may be very large. Fault trees (FTs) are a well-established industrial technique to represent causalities for possible system hazards resulting from system or system component failures. In this paper we suggest a method to automatically derive FTs from counterexamples, including a mapping of the probability information onto the FT. We extend the structural equation approach by Pearl and Halpern, which is based on Lewis counterfactuals, so that it serves as a justi cation for the causality that our proposed FT derivation rules imply. The synthesized FTs provide the user with a concise and compact representation of the causes of potential system failures, together with their respective probabilities. We demonstrate the usefulness of our approach by applying it to a selection of industrial size case studies.