Fastsat

Fastsat is a label commonly used in the field of automated reasoning to describe methods and tools designed to solve the Boolean satisfiability problem (SAT) as quickly as possible. There is no single universal software product named "fastsat"; rather the term has been used by multiple independent projects and in academic literature to denote speed-oriented SAT solvers or configurations.

SAT solvers determine if a propositional formula in conjunctive normal form is satisfiable and, more usefully, provide a satisfying assignment or a proof of unsatisfiability. Fastsat approaches emphasize speed through algorithmic innovations such as conflict-driven clause learning (CDCL), variable activity heuristics, restart policies, clause database management, preprocessing, and inprocessing techniques. Many fastsat implementations also employ parallelism or portfolios, running multiple strategies concurrently to cover diverse formula structures.

Applications for fastsat typically include formal verification, model checking, automated reasoning, constraint solving, and hardware and software design. These solvers are commonly evaluated on benchmark suites and in SAT solver competitions, where performance is measured in time to solve instances and memory usage. The term does not refer to a single standardized technology, and different projects may implement different features, interfaces, and licensing terms.

History and variants: The name fastsat has appeared in various open-source and commercial solvers; features and interfaces vary by version. When encountering a reference to fastsat, it is important to identify the exact solver and release to understand its capabilities and licensing.