Departmental Papers (CIS)
Document Type
Conference Paper
Date of this Version
July 2005
Abstract
The verification problem for a system consisting of components can be decomposed into simpler subproblems for the components using assume-guarantee reasoning. However, such compositional reasoning requires user guidance to identify appropriate assumptions for components. In this paper, we propose an automated solution for discovering assumptions based on the L* algorithm for active learning of regular languages. We present a symbolic implementation of the learning algorithm, and incorporate it in the model checker NuSMV. Our experiments demonstrate significant savings in the computational requirements of symbolic model checking.
COinS
Date Posted: 02 November 2005
Comments
Postprint version. Published in Lecture Notes in Computer Science, Volume 3576, 17th International Conference on Computer Aided Verification, CAV 2005, pages 548-562.
Publisher URL: http://dx.doi.org/10.1007/11513988_52