Exploring Predictability of SAT/SMT Solvers
نویسندگان
چکیده
This paper seeks to explore the predictability of SAT and SMT solvers in response to different kinds of changes to benchmarks. We consider both semantics-preserving and possibly semanticsmodifying transformations, and provide preliminary data about solver predictability. We also propose carrying learned theory lemmas over from an original run to runs on similar benchmarks, and show the benefits of this idea as a heuristic for improving predictability of SMT solvers.
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