Automated Abstraction Refinement for Model Checking Large State Spaces Using SAT Based Conflict Analysis

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. The main contribution of this paper are 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.

This research is sponsored by the Semiconductor Research Corporation (SRC) under contract no. 99-TJ-684, the Gigascale Silicon Research Center (GSRC), the National Science Foundation (NSF) under Grant No. CCR-9803774, and the Max Kade Foundation. One of the authors is also supported by Austrian Science Fund Project N Z29-INF. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of SRC, GSRC, NSF, or the United States Government.