Abstract
We introduce a SAT based automatic abstraction refinement framework for model checking systems with several thousand state variables in the cone of influence of the specification. The abstract model is constructed by designating a large number of state variables as “invisible”. In contrast to previous work where invisible variables were treated as free inputs we describe a computationally more advantageous approach in which the abstract transition relation is approximated by “pre-quantifying” invisible variables during image computation. The abstract counterexamples obtained from model-checking the abstract model are symbolically simulated on the concrete system using a state-of-the-art SAT checker. If no concrete counterexample is found, a subset of the invisible variables is reintroduced into the system and the process is repeated.
We discuss two new algorithms for identifying the relevant variables to be reintroduced. These algorithms monitor the SAT checking phase in order to analyze the impact of individual variables. Our method is complete for safety properties AG p in the sense that – performance permitting – a property is either verified or disproved by a concrete counterexample. Experimental results are given to demonstrate the power of our method on real-world designs.
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© 2003 Springer-Verlag Berlin Heidelberg
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Clarke, E.M. (2003). SAT-Based Counterexample Guided Abstraction Refinement in Model Checking. In: Baader, F. (eds) Automated Deduction – CADE-19. CADE 2003. Lecture Notes in Computer Science(), vol 2741. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45085-6_1
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DOI: https://doi.org/10.1007/978-3-540-45085-6_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40559-7
Online ISBN: 978-3-540-45085-6
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