Departmental Papers (CIS)

Date of this Version

10-2006

Document Type

Conference Paper

Comments

From the 4th International Symposium, ATVA 2006, Beijing, China, October 23-26, 2006.

Abstract

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.

Subject Area

CPS Formal Methods

Publication Source

Lecture Notes in Computer Science: Automated Technology for Verification and Analysis

Volume

4218

Start Page

170

Last Page

185

DOI

10.1007/11901914_15

Copyright/Permission Statement

The original publication is available at www.springerlink.com

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Date Posted: 26 June 2012