Reconsidering CEGAR: Learning Good Abstractions without Refinement
ICCD '05 Proceedings of the 2005 International Conference on Computer Design
Effective heuristics for counterexample-guided abstraction refinement
Proceedings of the 17th ACM Great Lakes symposium on VLSI
Abstraction and refinement techniques in automated design debugging
Proceedings of the conference on Design, automation and test in Europe
A Symbolic Model Checking Framework for Safety Analysis, Diagnosis, and Synthesis
Model Checking and Artificial Intelligence
Relaxation Refinement: A New Method to Generate Heuristic Functions
Model Checking and Artificial Intelligence
Boundary Points and Resolution
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Automated design debugging with abstraction and refinement
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Underapproximation for model-checking based on universal circuits
Information and Computation
Underapproximation for model-checking based on random cryptographic constructions
CAV'07 Proceedings of the 19th international conference on Computer aided verification
Managing complexity in design debugging with sequential abstraction and refinement
Proceedings of the 16th Asia and South Pacific Design Automation Conference
Abstraction-based algorithm for 2QBF
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
Making abstraction-refinement efficient in model checking
COCOON'11 Proceedings of the 17th annual international conference on Computing and combinatorics
An abstraction-refinement framework for trigger querying
SAS'11 Proceedings of the 18th international conference on Static analysis
A probabilistic learning approach for counterexample guided abstraction refinement
ATVA'06 Proceedings of the 4th international conference on Automated Technology for Verification and Analysis
An efficient approach for abstraction-refinement in model checking
Theoretical Computer Science
Detecting spurious counterexamples efficiently in abstract model checking
Proceedings of the 2013 International Conference on Software Engineering
Complexity-sensitive decision procedures for abstract argumentation
Artificial Intelligence
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We describe new techniques for model checking in the counterexample-guided abstraction-refinement framework. The abstraction phase "hides" the logic of various variables, hence considering them as inputs. This type of abstraction may lead to "spurious" counterexamples, i.e., traces that cannot be simulated on the original (concrete) machine. We check whether a counterexample is real or spurious with a satisfiability (SAT) checker. We then use a combination of 0-1 integer linear programming and machine learning techniques for refining the abstraction based on the counterexample. The process is repeated until either a real counterexample is found or the property is verified. We have implemented these techniques on top of the model checker NuSMV and the SAT solver Chaff. Experimental results prove the viability of these new techniques.