Scalable reachability analysis via automated dynamic netlist-based hint generation

While SAT-based algorithms have largely displaced BDD-based verification techniques due to their typically higher scalability, there are classes of problems for which BDDbased reachability analysis is the only existing method for an automated solution. Nonetheless, reachability engines require a high degree of tuning to perform well on challenging benchmarks. In addition to clever partitioning and scheduling techniques, the use of hints has been proposed to decompose an otherwise breadth-first fixedpoint computation into a series of underapproximate computations, requiring a larger number of (pre-)image iterations though often significantly reducing peak BDD size and thus resource requirements. In this paper, we introduce a novel approach to boost the scalability of reachability computation: automated netlist-based hint generation. Experiments confirm that this approach can yield significant resource reductions; often over an order of magnitude on complex problems compared to reachability analysis without hints, and even compared to SAT-based proof techniques.