State Caching Reconsidered [chapter]

Jaco Geldenhuys
2004 Lecture Notes in Computer Science  
State caching makes the full exploration of large state spaces possible by storing only a subset of the reachable states. While memory requirements are limited, the time consumption can increase dramatically if the subset is too small. It is often claimed that state caching is effective when the cache is larger than between 33% and 50% of the total state space, and that random replacement of cached states is the best strategy. Both these ideas are re-investigated in this paper. In addition, the
more » ... paper introduces a new technique, stratified caching, that reduces time consumption by placing an upper bound on the extra work caused by state caching. This, and a variety of other strategies are evaluated for random graphs and graphs based on actual verification models. Measurements made with Spin are presented.
doi:10.1007/978-3-540-24732-6_3 fatcat:3gdwoa4bubcq3az7sstnvwgacu