Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Learning regular sets from queries and counterexamples
Information and Computation
Model checking and modular verification
ACM Transactions on Programming Languages and Systems (TOPLAS)
Inference of finite automata using homing sequences
Information and Computation
ACM Transactions on Programming Languages and Systems (TOPLAS)
Multilevel hypergraph partitioning: applications in VLSI domain
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Multilevel k-way hypergraph partitioning
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
Formal Methods in System Design - Special issue on The First Federated Logic Conference (FLOC'96), part II
A Proof Technique for Rely/Guarantee Properties
Proceedings of the Fifth Conference on Foundations of Software Technology and Theoretical Computer Science
A Compositional Rule for Hardware Design Refinement
CAV '97 Proceedings of the 9th International Conference on Computer Aided Verification
NuSMV 2: An OpenSource Tool for Symbolic Model Checking
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
Learning assumptions for compositional verification
TACAS'03 Proceedings of the 9th international conference on Tools and algorithms for the construction and analysis of systems
Dynamic component substitutability analysis
FM'05 Proceedings of the 2005 international conference on Formal Methods
Symbolic compositional verification by learning assumptions
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
Learning-based assume-guarantee verification (tool paper)
SPIN'05 Proceedings of the 12th international conference on Model Checking Software
Learning to divide and conquer: applying the L* algorithm to automate assume-guarantee reasoning
Formal Methods in System Design
Verification of evolving software via component substitutability analysis
Formal Methods in System Design
Automatic symbolic compositional verification by learning assumptions
Formal Methods in System Design
Assume-Guarantee Verification for Interface Automata
FM '08 Proceedings of the 15th international symposium on Formal Methods
Decomposition for Compositional Verification
ICFEM '08 Proceedings of the 10th International Conference on Formal Methods and Software Engineering
Automated interface refinement for compositional verification
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Refining interface alphabets for compositional verification
TACAS'07 Proceedings of the 13th international conference on Tools and algorithms for the construction and analysis of systems
SAT-based compositional verification using lazy learning
CAV'07 Proceedings of the 19th international conference on Computer aided verification
Assume-guarantee reasoning with local specifications
ICFEM'10 Proceedings of the 12th international conference on Formal engineering methods and software engineering
A compositional minimization approach for large asynchronous design verification
SPIN'12 Proceedings of the 19th international conference on Model Checking Software
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Compositional reasoning aims to improve scalability of verification tools by reducing the original verification task into subproblems. The simplification is typically based on the assume-guarantee reasoning 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 heuristic 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.