SMT Solver
SMT (Satisfiability Modulo Theories) solvers are automated reasoning tools that determine the satisfiability of logical formulas with respect to background theories, such as arithmetic, arrays, or bit-vectors. They combine SAT (Boolean satisfiability) solving with theory-specific reasoning to handle complex constraints in software verification, program analysis, and formal methods. These solvers are widely used in areas like symbolic execution, test case generation, and hardware verification.
Developers should learn SMT solvers when working on formal verification, automated theorem proving, or constraint-solving tasks, such as in software testing (e.g., generating inputs to cover all paths) or security analysis (e.g., finding vulnerabilities through symbolic methods). They are essential in domains like compiler optimization, where proving correctness of transformations is required, and in AI planning or scheduling problems that involve logical constraints.