Minimal Coverability Tree Construction Made Complete and Efficient

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Abstract

Downward closures of Petri net reachability sets can be finitely represented by their set of maximal elements called the minimal coverability set or Clover. Many properties (coverability, boundedness,..) can be decided using Clover, in a time proportional to the size of Clover. So it is crucial to design algorithms that compute it efficiently. We present a simple modification of the original but incomplete Minimal Coverability Tree algorithm (MCT), computing Clover, which makes it complete: it memorizes accelerations and fires them as ordinary transitions. Contrary to the other alternative algorithms for which no bound on the size of the required additional memory is known, we establish that the additional space of our algorithm is at most doubly exponential. Furthermore we have implemented a prototype MinCov which is already very competitive: on benchmarks it uses less space than all the other tools and its execution time is close to the one of the fastest tool.

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APA

Finkel, A., Haddad, S., & Khmelnitsky, I. (2020). Minimal Coverability Tree Construction Made Complete and Efficient. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12077 LNCS, pp. 237–256). Springer. https://doi.org/10.1007/978-3-030-45231-5_13

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