Date of this Version
Wonhong Nam and Rajeev Alur, "Learning-Based Symbolic Assume-Guarantee Reasoning With Automatic Decomposition", Lecture Notes in Computer Science: Automated Technology for Verification and Analysis 4218, 170-185. October 2006. http://dx.doi.org/10.1007/11901914_15
Compositional reasoning aims to improve scalability of veri- fication tools by reducing the original verification task into subproblems. The simplification is typically based on the assume-guarantee reason- ing principles, and requires decomposing the system into components as well as identifying adequate environment assumptions for components. One recent approach to automatic derivation of adequate assumptions is based on the L* algorithm for active learning of regular languages. In this paper, we present a fully automatic approach to compositional reasoning by automating the decomposition step using an algorithm for hypergraph partitioning for balanced clustering of variables. We also propose heuris- tic improvements to the assumption identification phase. We report on an implementation based on NuSMV, and experiments that study the effectiveness of automatic decomposition and the overall savings in the computational requirements of symbolic model checking.
CPS Formal Methods
Lecture Notes in Computer Science: Automated Technology for Verification and Analysis
The original publication is available at www.springerlink.com
Date Posted: 26 June 2012