Modular Partitioning and Dynamic Conjunction Scheduling in Image Computation

Image computation is the core task in any formal verification applications like reachable states computation or model checking. In OBDD-based image computation a partitioned representation of the transition relation is used. The quality of the partitioning and the schedule in which the partitions are processed is crucial for the efficiency of the image computation. In this paper we describe an approach to build a hierarchical modular partitioned transition relation. Based on this partitioning we present a dynamic conjunction scheduling algorithm that improves the flexibility and computational power of the image computation. The concept is proven by symbolic model checking experiments.