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Sound and Precise Symbolic Automata Model for Stateful Software Systems

Xinlong Wu, Ruiyu Zhou, Peisen Yao, Qingkai Shi

Abstract

Abstract Verifying stateful software systems remains challenging due to complex control structures and intricate state interactions, often necessitating pre-existing behavioral models. We introduce , an abstract interpreter that automatically derives sound and precise symbolic finite automata models. In tests on real-world applications, generates sound and precise automata within minutes and, when employed in dynamic model checking, achieves 1.6 $$\times $$ × –3.4 $$\times $$ × code coverage compared to the state of the art. These findings demonstrate that can effectively connect code to model-based verification for stateful software systems.

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