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-reviewPublication Information
Output type
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-reviewOriginal language
EnglishJournal (Volume, Issue Number)
ACM Transactions on Embedded Computing Systems (Volume 13, Issue 4s)Publication milestones
- Published - 2014
Publication status
Published - 2014
ISSN
1539-9087Publication 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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