Model checking, abstraction, and compositional verification
Model checking, abstraction, and compositional verification
Automatic predicate abstraction of C programs
Proceedings of the ACM SIGPLAN 2001 conference on Programming language design and implementation
Construction of Abstract State Graphs with PVS
CAV '97 Proceedings of the 9th International Conference on Computer Aided Verification
Counterexample-Guided Abstraction Refinement
CAV '00 Proceedings of the 12th International Conference on Computer Aided Verification
SAT Based Abstraction-Refinement Using ILP and Machine Learning Techniques
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Boolean and Cartesian Abstraction for Model Checking C Programs
TACAS 2001 Proceedings of the 7th International Conference on Tools and Algorithms for the Construction and Analysis of Systems
Successive Approximation of Abstract Transition Relations
LICS '01 Proceedings of the 16th Annual IEEE Symposium on Logic in Computer Science
Improving Ariadne's Bundle by Following Multiple Threads in Abstraction Refinement
Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
Iterative Abstraction using SAT-based BMC with Proof Analysis
Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
Lazy Constraints and SAT Heuristics for Proof-Based Abstraction
VLSID '05 Proceedings of the 18th International Conference on VLSI Design held jointly with 4th International Conference on Embedded Systems Design
Word level predicate abstraction and refinement for verifying RTL verilog
Proceedings of the 42nd annual Design Automation Conference
Dynamic abstraction using SAT-based BMC
Proceedings of the 42nd annual Design Automation Conference
Proceedings of the conference on Design, automation and test in Europe
VCEGAR: Verilog counterexample guided abstraction refinement
TACAS'07 Proceedings of the 13th international conference on Tools and algorithms for the construction and analysis of systems
Automatic abstraction without counterexamples
TACAS'03 Proceedings of the 9th international conference on Tools and algorithms for the construction and analysis of systems
Localization and register sharing for predicate abstraction
TACAS'05 Proceedings of the 11th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Abstract Model Checking without Computing the Abstraction
FM '09 Proceedings of the 2nd World Congress on Formal Methods
An automatic method for the dynamic construction of abstractions of states of a formal model
Cybernetics and Systems Analysis
Trace-driven verification of multithreaded programs
ICFEM'10 Proceedings of the 12th international conference on Formal engineering methods and software engineering
Computing small unsatisfiable cores in satisfiability modulo theories
Journal of Artificial Intelligence Research
Property-specific sequential invariant extraction for SAT-based unbounded model checking
Proceedings of the International Conference on Computer-Aided Design
Word level feature discovery to enhance quality of assertion mining
Proceedings of the International Conference on Computer-Aided Design
Generating concise assertions with complete coverage
Proceedings of the 23rd ACM international conference on Great lakes symposium on VLSI
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Variable hiding and predicate abstraction are two popular abstraction methods to obtain simplified models for model checking. Although both methods have been used successfully in practice, no attempt has been made to combine them in counterexample guided abstraction refinement (CEGAR). In this paper, we propose a hybrid abstraction method that allows both visible variables and predicates to take advantages of their relative strengths. We use refinement based on weakest preconditions to add new predicates, and under certain conditions trade in the predicates for visible variables in the abstract model. We also present heuristics for improving the overall performance, based on static analysis to identify useful candidates for visible variables, and use of lazy constraints to find more effective unsatisfiable cores for refinement. We have implemented the proposed hybrid CEGAR procedure. Our experiments on public benchmarks show that the new abstraction method frequently outperforms the better of the two existing abstraction methods.