This paper describes a probabilistic approach to state space search. The presented method applies a ranking of the design states according to their probability of reaching a given target state based on a random walk model. This ranking can be used to prioritize an explicit or partial symbolic state exploration to find a trajectory from a set of initial states to a set of target states. A symbolic technique for estimating the reachability probability is described which implements a smooth trade-off between accuracy and computing effort. The presented probabilistic state space search complements incomplete verification methods which are specialized in finding errors in large designs.
Andreas Kuehlmann, Kenneth L. McMillan, Robert K.