Heuristics for Selecting Predicates for Partial Predicate Abstraction
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by
Tuba Yavuz, Chelsea Metcalf
2017
Abstract
In this paper we consider the problem of configuring partial predicate
abstraction that combines two techniques that have been effective in analyzing
infinite-state systems: predicate abstraction and fixpoint approximations. A
fundamental problem in partial predicate abstraction is deciding the variables
to be abstracted and the predicates to be used. In this paper, we consider
systems modeled using linear integer arithmetic and investigate an alternative
approach to counter-example guided abstraction refinement. We devise two
heuristics that search for predicates that are likely to be precise. The first
heuristic performs the search on the problem instance to be verified. The other
heuristic leverages verification results on the smaller instances of the
problem. We report experimental results for CTL model checking and discuss
advantages and disadvantages of each approach.
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