Incremental Bisimulation Abstraction Refinement
Lei Song, Lijun Zhang, Holger Hermanns, Jens Chr. Godskesen · ACM Transactions on Embedded Computing Systems · 2014
Abstraction refinement techniques in probabilistic model checking are prominent approaches for 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 article 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.