Hierarchical Set Decision Diagrams and Regular Models

Abstract : This paper presents algorithms and data structures that exploit a compositional and hierarchical specification to enable more efficient symbolic model-checking. We encode the state space and transition relation using hierarchical Set Decision Diagrams (SDD) [9].In SDD, arcs of the structure are labeled with sets, themselves stored as SDD. To exploit the hierarchy of SDD, a structured model representation is needed. We thus introduce a formalism integrating a simple notion of type and instance. Complex composite behaviors are obtained using a synchronization mechanism borrowed from process calculi. Using this relatively general framework, we investigate how to capture similarities in regular and concurrent models. Experimental results are presented, showing that this approach can outperform in time and memory previous work in this area.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01294397
Contributor : Lip6 Publications <>
Submitted on : Tuesday, March 29, 2016 - 11:22:36 AM
Last modification on : Wednesday, May 15, 2019 - 3:47:33 AM

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Yann Thierry-Mieg, Denis Poitrenaud, Alexandre Hamez, Fabrice Kordon. Hierarchical Set Decision Diagrams and Regular Models. 15th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS), Mar 2009, York, United Kingdom. pp.1-15, ⟨10.1007/978-3-642-00768-2_1⟩. ⟨hal-01294397⟩

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