An O(m log n) algorithm for branching bisimilarity on labelled transition systems

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Abstract

Branching bisimilarity is a behavioural equivalence relation on labelled transition systems (LTSs) that takes internal actions into account. It has the traditional advantage that algorithms for branching bisimilarity are more efficient than ones for other weak behavioural equivalences, especially weak bisimilarity. With m the number of transitions and n the number of states, the classic O(mn) algorithm was recently replaced by an O(m(log |Act | + log n)) algorithm [9], which is unfortunately rather complex. This paper combines its ideas with the ideas from Valmari [20], resulting in a simpler O(mlog n) algorithm. Benchmarks show that in practice this algorithm is also faster and often far more memory efficient than its predecessors, making it the best option for branching bisimulation minimisation and preprocessing for calculating other weak equivalences on LTSs.

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Jansen, D. N., Groote, J. F., Keiren, J. J. A., & Wijs, A. (2020). An O(m log n) algorithm for branching bisimilarity on labelled transition systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12079 LNCS, pp. 3–20). Springer. https://doi.org/10.1007/978-3-030-45237-7_1

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