Automated assumption generation for compositional verification

摘要

We describe a method for computing a minimum-state automaton to act as an intermediate assertion in assume-guarantee reasoning, using a sampling approach and a Boolean satisfiability solver. For a set of synthetic benchmarks intended to mimic common situations in hardware verification, this is shown to be significantly more effective than earlier approximate methods based on Angluin's L~* algorithm. For many of these benchmarks, this method also outperforms BDD-based model checking and interpolation-based model checking. We also demonstrate how domain knowledge can be incorporated into our algorithm to improve its performance.