Model-Checking with Insufficient Memory Resources

Resource limitations is a major problem in model checking. Space and time requirements of model-checking algorithms grow exponentially with respect to the number of variables and parallel automata of the analyzed model. We present a method that is the result of experiences from a case study. It has enabled us to analyze models with much bigger state-spaces than what was possible without our method. The basic idea is to build partitions of the state-space of an analyzed system by iterative invocations of a model-checker. In each iteration the partitions are extended to represent a larger part of the state space, and if needed the partitions are further partitioned. Thereby the analysis problem is divided into a set of subproblems that can be analyzed independently of each other. We present how the method, implemented as a meta algorithm on-top of the Uppaal tool, has been applied in the case study.