Probabilistic fault tree synthesis using causality computation

Abstract

In recent years, several approaches to generate probabilistic counterexamples have been proposed. The interpretation of probabilistic 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 extend the structural equation approach by Pearl and Halpern, which is based on Lewis counterfactuals, so that it can be applied to reason about causalities in a state-action trace model induced by a probabilistic counterexample. The causality relationships derived by the extended structural equation model are then mapped onto fault trees. We demonstrate the usefulness of our approach by applying it to a selection of case studies known from literature.