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Incremental Bisimulation Abstraction Refinement

  • Lei Song
    ,
  • Holger Hermanns
    ,
  • Lijun Zhang
  • Saarland University
    ,
  • Chinese Academy of Sciences
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-review

Publication Information

Output type

Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-review

Original language

English

Journal (Volume, Issue Number)

ACM Transactions on Embedded Computing Systems (Volume 13, Issue 4s)

Publication milestones

  • Published - 2014

Publication status

Published - 2014

ISSN

1539-9087

Publication IDs

  • Scopus: 84995595396

Abstract

Abstraction refinement techniques in probabilistic model checking are prominent approaches to the verification of very large or infinite-state probabilistic concurrent systems. At the core of the refinement step lies the implicit or explicit analysis of a counterexample. This paper proposes an abstraction refinement approach for the probabilistic computation tree logic (PCTL), which is based on incrementally computing a sequence of may- and must-quotient automata. These are induced by depth-bounded bisimulation equivalences of increasing depth. The approach is both sound and complete, since the equivalences converge to the genuine PCTL equivalence. Experimental results with a prototype implementation show the effectiveness of the approach.

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