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International Symposium on Model Checking Software

SPIN 2018: Model Checking Software pp 103–114Cite as

Star-Topology Decoupling in SPIN

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10869))

Abstract

Star-topology decoupling is a state space search method recently introduced in AI Planning. It decomposes the input model into components whose interaction structure has a star shape. The decoupled search algorithm enumerates transition paths only for the center component, maintaining the leaf-component state space separately for each leaf. This is a form of partial-order reduction, avoiding interleavings across leaf components. It can, and often does, have exponential advantages over stubborn set pruning and unfolding. AI Planning relates closely to model checking of safety properties, so the question arises whether decoupled search can be successful in model checking as well. We introduce a first implementation of star-topology decoupling in SPIN, where the center maintains global variables while the leaves maintain local ones. Preliminary results on several case studies attest to the potential of the approach.

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Acknowledgments

Daniel Gnad was partially supported by the German Research Foundation (DFG), as part of project grant HO 2169/6-1, “Star-Topology Decoupled State Space Search”.

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Authors and Affiliations

  1. Saarland Informatics Campus, Saarland University, Saarbrücken, Germany

    Daniel Gnad, Patrick Dubbert & Jörg Hoffmann

  2. Technical University of Denmark, Kongens Lyngby, Denmark

    Alberto Lluch Lafuente

Authors
  1. Daniel Gnad
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  2. Patrick Dubbert
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  3. Alberto Lluch Lafuente
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  4. Jörg Hoffmann
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Corresponding author

Correspondence to Daniel Gnad .

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Editors and Affiliations

  1. University of Málaga, Málaga, Spain

    María del Mar Gallardo

  2. University of Málaga, Málaga, Spain

    Pedro Merino

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Gnad, D., Dubbert, P., Lluch Lafuente, A., Hoffmann, J. (2018). Star-Topology Decoupling in SPIN. In: Gallardo, M., Merino, P. (eds) Model Checking Software. SPIN 2018. Lecture Notes in Computer Science(), vol 10869. Springer, Cham. https://doi.org/10.1007/978-3-319-94111-0_6

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  • DOI: https://doi.org/10.1007/978-3-319-94111-0_6

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