Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Symbolic model checking: 1020 states and beyond
Information and Computation - Special issue: Selections from 1990 IEEE symposium on logic in computer science
Safe BDD minimization using don't cares
DAC '97 Proceedings of the 34th annual Design Automation Conference
Construction of Abstract State Graphs with PVS
CAV '97 Proceedings of the 9th International Conference on Computer Aided Verification
Counterexample-guided abstraction refinement for symbolic model checking
Journal of the ACM (JACM)
Word level predicate abstraction and refinement for verifying RTL verilog
Proceedings of the 42nd annual Design Automation Conference
Proceedings of the conference on Design, automation and test in Europe
Computing Predicate Abstractions by Integrating BDDs and SMT Solvers
FMCAD '07 Proceedings of the Formal Methods in Computer Aided Design
CAV '08 Proceedings of the 20th international conference on Computer Aided Verification
SMT techniques for fast predicate abstraction
CAV'06 Proceedings of the 18th international conference on Computer Aided Verification
Predicate abstraction via symbolic decision procedures
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
Building efficient decision procedures on top of SAT solvers
SFM'06 Proceedings of the 6th international conference on Formal Methods for the Design of Computer, Communication, and Software Systems
KRATOS: a software model checker for SystemC
CAV'11 Proceedings of the 23rd international conference on Computer aided verification
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We address the problem of computing the exact abstraction of a program with respect to a given set of predicates, a key computation step in Counter-Example Guided Abstraction Refinement. We build on a recently proposed approach that integrates BDD-based quantification techniques with SMT-based constraint solving to compute the abstraction. We extend the previous work in three main directions. First, we propose a much tighter integration of the BDD-based and SMT-based reasoning where the two solvers strongly collaborate to guide the search. Second, we propose a technique to reduce redundancy in the search by blocking already visited models. Third, we present an algorithm exploiting a conjunctively partitioned representation of the formula to quantify. This algorithm provides a general framework where all the presented optimizations integrate in a natural way. Moreover, it allows to overcome the limitations of the original approach that used a monolithic BDD representation of the formula to quantify. We experimentally evaluate the merits of the proposed optimizations, and show how they allow to significantly improve over previous approaches.