Satisfiability solvers, often referred to as SAT solvers, are algorithms designed to determine if a given logical formula can be satisfied by some assignment of truth values to its variables. They are primarily used in fields like computer science, artificial intelligence, and formal verification to solve problems expressed in propositional logic. These solvers work by exploring possible combinations of variable assignments to find at least one that makes the entire formula true. Popular techniques used in SAT solvers include DPLL (Davis-Putnam-Logemann-Loveland) and CDCL (Conflict-Driven Clause Learning), which enhance efficiency in solving complex problems.