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Hierarchical Set Decision Diagrams and Regular Models

  • Yann Thierry-Mieg
  • Denis Poitrenaud
  • Alexandre Hamez
  • Fabrice Kordon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5505)

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.

Keywords

Transition Relation Transitive Closure Label Transition System Binary Decision Diagram Homomorphism Encode 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Yann Thierry-Mieg
    • 1
  • Denis Poitrenaud
    • 1
  • Alexandre Hamez
    • 1
  • Fabrice Kordon
    • 1
  1. 1.Université P. & M. Curie-LIP6 - CNRS UMR 7606ParisFrance

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