Making Abstraction Refinement Efficient in Model Checking
Cong Tian, Zhenhua Duan
Abstract
Open-access reader
Cong Tian, Zhenhua Duan
Abstract
Open-access reader
Abstraction is one of the most important strategies for dealing with the state space explosion problem in model checking. In the abstract model, although the state space is largely reduced, however, a counterexample found in such a model may not be a real counterexample. And the abstract model needs to be further refined where an NP-hard state separation problem is often involved. In this paper, a novel method is presented by adding extra variables to the abstract model for the refinement. With this method, not only the NP-hard state separation problem is avoided, but also a smaller refined abstract model is obtained.
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Abstraction is one of the most important strategies for dealing with the state space explosion problem in model checking. In the abstract model, although the state space is largely reduced, however, a counterexample found in such a model may not be a real counterexample. And the abstract model needs to be further refined where an NP-hard state separation problem is often involved. In this paper, a novel method is presented by adding extra variables to the abstract model for the refinement. With this method, not only the NP-hard state separation problem is avoided, but also a smaller refined abstract model is obtained.
Key concepts: Counterexample, Abstraction, Model checking, Abstraction model checking, State space, Computer science, State (computer science), Theoretical computer science