Generation of Minimum-Consistent DFA Using SAT Solver

Exact DFA Identification Using SAT Solvers

We present an exact algorithm for identification of deterministic finite automata (DFA) which is based on satisfiability (SAT) solvers. Despite the size of the low level SAT representation, our approach is competitive with alternative techniques. Our contributions are fourfold: First, we propose a compact translation of DFA identification into SAT. Second, we reduce the SAT search space by addi...

Minimal consistent DFA revisited

Progressive Generation of Canonical Sums of Products Using a SAT Solver

We present an algorithm that progressively generates canonical Sums Of Products (SOPs) for completelyand incompletely-specified Boolean functions using a satisfiability solver. The progressive generation allows for real time monitoring and early termination, as well as for generation of partial SOPs for specific incremental applications. On the other hand, canonicity brings independence of the ...

Eureka-2008 SAT Solver

We describe the SAT solver Eureka. Eureka is a state-of-the-art SAT solver, used in various Formal Verification flows at Intel. Eureka is based upon backtrack search DLL algorithm, enhanced by failure-driven assertion loop; nonstandard conflict analyses; restart and clause deletion strategies; CBH decision heuristic and decision stack shrinking.

An Adaptive SAT Solver

This proposal outlines the creation of an adaptive algorithm for the Propositional Satisfiability Problem (SAT). The SAT problem is of great importance in theoretical computer science and verification. The proposed algorithm, or solver, uses the well-known DPLL approach coupled with a variety of optimizations and extensions which are selectively turned on and off during runtime to adapt to the ...