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Early Results with Precision Abstraction: Using Data-flow Analysis to Improve the Scalability of Model Checking

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3 Author(s)
Brown, A. ; Dept. of Comput. Sci., Texas Univ., Austin, TX ; Browne, J.C. ; Lin, C.

This paper presents a new state space reduction technique that applies to model checking of software. The new technique, precision abstraction, borrows ideas from dataflow analysis to identify procedures that can be analyzed context-insensitively without affecting the accuracy of the verification of a given property. These context-insensitive procedures can then be represented with fewer states than would be needed context-sensitive analysis. Preliminary results indicate that the number of transitions in the analysis prescribed by our approach is at least 155 times fewer than the exhaustive analysis a model checker would otherwise perform.

Published in:

Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International

Date of Conference:

26-30 March 2007