Improving Saturation Efficiency with Implicit Relations

Abstract

Decision diagrams are a well-established data structure for reachability set generation and model checking of high-level models such as Petri nets, due to their versatility and the availability of efficient algorithms for their construction. Using a decision diagram to represent the transition relation of each event of the high-level model, the saturation algorithm can be used to construct a decision diagram representing all states reachable from an initial set of states, via the occurrence of zero or more events. A difficulty arises in practice for models whose state variable bounds are unknown, as the transition relations cannot be constructed before the bounds are known. Previously, on-the-fly approaches have constructed the transition relations along with the reachability set during the saturation procedure. This can affect performance, as the transition relation decision diagrams must be rebuilt, and compute-table entries may need to be discarded, as the size of each state variable increases. In this paper, we introduce a different approach based on an implicit and unchanging representation for the transition relations, thereby avoiding the need to reconstruct the transition relations and discard compute-table entries. We modify the saturation algorithm to use this new representation, and demonstrate its effectiveness with experiments on several benchmark models.