Automated reasoning (AR) is a field of computer science concerned with turning computers into ever smarter thinking machines, and injecting reasoning into computer applications. AR is artificial intelligence (AI), symbolic computation (SC), computational logic (CL), and it contributes to the fundamental quest about what computing machines can do. To date AR has developed primarily deductive methods that build proofs (an argument by which something follows from something) or models (e.g., a solution to a set of constraints, a counterexample), and can be applied to settle conjectures about systems (e.g., programs, circuits, data structures, communication protocols, mathematical structures). Automated reasoners include theorem provers, proof assistants, model builders, validity checkers, SAT-solvers (for SATisfiability in propositional logic), SMT-solvers (Satisfiability Modulo Theories), model checkers, and proof checkers, complemented with libraries of theorems, and knowledge bases of computer-checked mathematics. These tools can be integrated to form reasoning environments or embedded as reasoning components inside other software systems. My research includes theory, implementation, and application, encompassing both synthetic (e.g., design of reasoning procedures), and analytic (e.g., analysis of their behavior) sides of computer science:

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Maria Paola Bonacina