Efficient Strategies for CEGAR-based Model Checking

TitleEfficient Strategies for CEGAR-based Model Checking
Publication TypeJournal Article
Year of Publication2020
AuthorsHajdu, Á., and Micskei, Z.
JournalJournal of Automated Reasoning
Volume64
Issue6
Pagination1051-1091
ISSN0168-7433
Abstract

Automated formal verification is often based on the Counterexample-Guided Abstraction Refinement (CEGAR) approach. Many variants of CEGAR have been developed over the years as different problem domains usually require different strategies for efficient verification. This has lead to generic and configurable CEGAR frameworks, which can incorporate various algorithms. In our paper we propose six novel improvements to different aspects of the CEGAR approach, including both abstraction and refinement. We implement our new contributions in the Theta framework allowing us to compare them with state-of-the-art algorithms. We conduct an experiment on a diverse set of models to address research questions related to the effectiveness and efficiency of our new strategies. Results show that our new contributions perform well in general. Moreover, we highlight certain cases where performance could not be increased or where a remarkable improvement is achieved.

URLhttps://link.springer.com/article/10.1007/s10817-019-09535-x
DOI10.1007/s10817-019-09535-x
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