Guided Model Checking with a Bayesian Meta-heuristic

Michael Jones
Peter Lamborn

Abstract

This paper presents a meta-heuristic for use in finding errors in models of complex concurrent systems using explicit guided model checking. The meta-heuristic improves explicit guided model checking by applying the empirical Bayes method to revise heuristic estimates of the distance from a given state to an error state. Guided search using the revised estimates finds errors with less search effort than the original estimates.