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Sat based abstraction-renement using ILP and machine learning techniques (2002)
| Venue: | In Proc. of Conference on Computer-Aided Verification (CAV’02), LNCS |
| Citations: | 1 - 1 self |
BibTeX
@INPROCEEDINGS{Clarke02satbased,
author = {Edmund Clarke and Anubhav Gupta and James Kukula and Ofer Strichman},
title = {Sat based abstraction-renement using ILP and machine learning techniques},
booktitle = {In Proc. of Conference on Computer-Aided Verification (CAV’02), LNCS},
year = {2002}
}
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Abstract
Abstract. We describe new techniques for model checking in the coun-terexample guided abstraction/renement framework. The abstraction phase `hides ' the logic of various variables, hence considering them as inputs. This type of abstraction may lead to `spurious ' counterexam-ples, i.e. traces that can not be simulated on the original (concrete) machine. We check whether a counterexample is real or spurious with a SAT checker. We then use a combination of Integer Linear Program-ming (ILP) and machine learning techniques for rening the abstraction based on the counterexample. The process is repeated until either a real counterexample is found or the property is veried. We have implemented these techniques on top of the model checker NuSMV and the SAT solver Cha. Experimental results prove the viability of these new techniques. 1
