Error detection with directed symbolic model checking

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Abstract

In practice due to entailed memory limitations the most important problem in model checking is state space explosion. Therefore, to prove the correctness of a given design binary decision diagrams (BDDs) are widely used as a concise and symbolic state space representation. Nevertheless, BDDs are not able to avoid an exponential blow-up in general.If we restrict ourselves to nd an error of a design which violates a safety property, in many cases a complete state space exploration is not necessary and the introduction of a heuristic to guide the search can help to keep both the explored part and the associated BDD representation smaller than with the classical approach. In this paper we will show that this idea can be extended with an automatically generated heuristic and that it is applicable to a large class of designs. Since the proposed algorithm can be expressed in terms of BDDs it is even possible to use an existent model checker without any internal changes.

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APA

Reel, F., & Edelkamp, S. (1999). Error detection with directed symbolic model checking. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1708, pp. 195–211). Springer Verlag. https://doi.org/10.1007/3-540-48119-2_13

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