Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
DAG-aware AIG rewriting a fresh look at combinational logic synthesis
Proceedings of the 43rd annual Design Automation Conference
Scalable exploration of functional dependency by interpolation and incremental SAT solving
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
An approach for extracting a small unsatisfiable core
Formal Methods in System Design
The analysis of cyclic circuits with Boolean satisfiability
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
Invariant-strengthened elimination of dependent state elements
Proceedings of the 2008 International Conference on Formal Methods in Computer-Aided Design
A clause-based heuristic for SAT solvers
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Discrete Applied Mathematics
The Synthesis of Cyclic Dependencies with Boolean Satisfiability
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Lemma localization: a practical method for downsizing SMT-interpolants
Proceedings of the Conference on Design, Automation and Test in Europe
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Craig Interpolation is a state-of-the-art technique for logic synthesis and verification, based on Boolean Satisfiability (SAT). Leveraging the efficacy of SAT algorithms, Craig Interpolation produces solutions quickly to challenging problems such as synthesizing functional dependencies and performing bounded model-checking. Unfortunately, the quality of the solutions is often poor. When interpolants are used to synthesize functional dependencies, the resulting structure of the functions may be unnecessarily complex. In most applications to date, interpolants have been generated directly from the proofs of unsatisfiability that are provided by SAT solvers. In this work, we propose efficient methods based on incremental SAT solving for modifying resolution proofs in order to obtain more compact interpolants. This, in turn, reduces the cost of the logic that is generated for functional dependencies.