Hierarchical Adaptive State Space Caching Based on Level Sampling
TACAS '09 Proceedings of the 15th International Conference on Tools and Algorithms for the Construction and Analysis of Systems: Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2009,
LTL translation improvements in Spot 1.0
International Journal of Critical Computer-Based Systems
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Explicit model checking algorithms explore the full state space of a system. State spaces are usually treated as directed graphs without any specific features. We gather a large collection of state spaces and extensively study their structural properties. Our results show that state spaces have several typical properties, i.e., they are not arbitrary graphs. We also demonstrate that state spaces differ significantly from random graphs and that different classes of models (application domains, academic vs. industrial) have different properties. We discuss consequences of these results for model checking experiments and we point out how to exploit typical properties of state spaces in practical model checking algorithms.