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A Parallel Relation-Based Algorithm for Symbolic Bisimulation Minimization

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Verification, Model Checking, and Abstract Interpretation (VMCAI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11388))

Abstract

Symbolic computation using BDDs and bisimulation minimization are alternative ways to cope with the state space explosion in model checking. The combination of both techniques opens up many parameters that can be tweaked for further optimization. Most importantly, the bisimulation can either be represented as equivalence classes or as a relation. While recent work argues that storing partitions is more efficient, we show that the relation-based approach is preferable. We do so by deriving a relation-based minimization algorithm based on new coarse-grained BDD operations. The implementation demonstrates that the relational approach uses fewer memory and performs better.

The second author is funded by the research program VENI with project number 639.021.649 of the Netherlands Organization for Scientific Research (NWO).

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Authors and Affiliations

  1. LIACS, Leiden University, Leiden, The Netherlands

    Richard Huybers & Alfons Laarman

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  1. Richard Huybers
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  2. Alfons Laarman
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Correspondence to Alfons Laarman .

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Editors and Affiliations

  1. IRIF, University Paris Diderot and CNRS, Paris, France

    Constantin Enea

  2. Yale University, New Haven, CT, USA

    Ruzica Piskac

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Huybers, R., Laarman, A. (2019). A Parallel Relation-Based Algorithm for Symbolic Bisimulation Minimization. In: Enea, C., Piskac, R. (eds) Verification, Model Checking, and Abstract Interpretation. VMCAI 2019. Lecture Notes in Computer Science(), vol 11388. Springer, Cham. https://doi.org/10.1007/978-3-030-11245-5_25

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  • DOI: https://doi.org/10.1007/978-3-030-11245-5_25

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  • Print ISBN: 978-3-030-11244-8

  • Online ISBN: 978-3-030-11245-5

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