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Journal of Computer and System Sciences - 26th IEEE Conference on Foundations of Computer Science, October 21-23, 1985
A fast algorithm for finding dominators in a flowgraph
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Pruning Techniques for the SAT-Based Bounded Model Checking Problem
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Proof-guided underapproximation-widening for multi-process systems
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Local-search Extraction of MUSes
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Deciding bit-vector arithmetic with abstraction
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
A simple and flexible way of computing small unsatisfiable cores in SAT modulo theories
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
A branch-and-bound algorithm for extracting smallest minimal unsatisfiable formulas
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
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CAV'06 Proceedings of the 18th international conference on Computer Aided Verification
A scalable algorithm for minimal unsatisfiable core extraction
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
HAIFASAT: a new robust SAT solver
HVC'05 Proceedings of the First Haifa international conference on Hardware and Software Verification and Testing
On Extending Bounded Proofs to Inductive Proofs
CAV '09 Proceedings of the 21st International Conference on Computer Aided Verification
An efficient and flexible approach to resolution proof reduction
HVC'10 Proceedings of the 6th international conference on Hardware and software: verification and testing
Compression of propositional resolution proofs via partial regularization
CADE'11 Proceedings of the 23rd international conference on Automated deduction
Flexible interpolation with local proof transformations
Proceedings of the International Conference on Computer-Aided Design
Two techniques for minimizing resolution proofs
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
Improved single pass algorithms for resolution proof reduction
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
Improved single pass algorithms for resolution proof reduction
ATVA'12 Proceedings of the 10th international conference on Automated Technology for Verification and Analysis
Lemma localization: a practical method for downsizing SMT-interpolants
Proceedings of the Conference on Design, Automation and Test in Europe
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Proceedings of the Conference on Design, Automation and Test in Europe
Efficient generation of small interpolants in CNF
CAV'13 Proceedings of the 25th international conference on Computer Aided Verification
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DPLL-based SAT solvers progress by implicitly applying binary resolution. The resolution proofs that they generate are used, after the SAT solver's run has terminated, for various purposes. Most notable uses in formal verification are: extracting an unsatisfiable core , extracting an interpolant , and detecting clauses that can be reused in an incremental satisfiability setting (the latter uses the proof only implicitly, during the run of the SAT solver). Making the resolution proof smaller can benefit all of these goals. We suggest two methods that are linear in the size of the proof for doing so. Our first technique, called Recycle-Units , uses each learned constant (unit clause) (x ) for simplifying resolution steps in which x was the pivot, prior to when it was learned. Our second technique, called Recycle-Pivots , simplifies proofs in which there are several nodes in the resolution graph, one of which dominates the others, that correspond to the same pivot. Our experiments with industrial instances show that these simplifications reduce the core by ≈ 5% and the proof by ≈ 13%. It reduces the core less than competing methods such as run-till-fix , but whereas our algorithms are linear in the size of the proof, the latter and other competing techniques are all exponential as they are based on SAT runs. If we consider the size of the proof graph as being polynomial in the number of variables (it is not necessarily the case in general), this gives our method an exponential time reduction comparing to existing tools for small core extraction. Our experiments show that this result is evident in practice more so for the second method: rarely it takes more than a few seconds, even when competing tools time out, and hence it can be used as a cheap proof post-processing procedure.