2010 | OriginalPaper | Buchkapitel
Automated Assume-Guarantee Reasoning through Implicit Learning
verfasst von : Yu-Fang Chen, Edmund M. Clarke, Azadeh Farzan, Ming-Hsien Tsai, Yih-Kuen Tsay, Bow-Yaw Wang
Erschienen in: Computer Aided Verification
Verlag: Springer Berlin Heidelberg
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We propose a purely implicit solution to the contextual assumption generation problem in assume-guarantee reasoning. Instead of improving the
L
*
algorithm — a learning algorithm for
finite automata
, our algorithm computes implicit representations of contextual assumptions by the CDNF algorithm — a learning algorithm for
Boolean functions
. We report three parametrized test cases where our solution outperforms the monolithic interpolation-based Model Checking algorithm.