16 research outputs found

    The Strategy Challenge in SMT Solving

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    Abstract. High-performance SMT solvers contain many tightly integrated, hand-crafted heuristic combinations of algorithmic proof methods. While these heuristic combinations tend to be highly tuned for known classes of problems, they may easily perform badly on classes of problems not anticipated by solver developers. This issue is becoming increasingly pressing as SMT solvers begin to gain the attention of practitioners in diverse areas of science and engineering. We present a challenge to the SMT community: to develop methods through which users can exert strategic control over core heuristic aspects of SMT solvers. We present evidence that the adaptation of ideas of strategy prevalent both within the Argonne and LCF theorem proving paradigms can go a long way towards realizing this goal. Prologue. Bill McCune, Kindness and Strategy, by Grant Passmore I would like to tell a short story about Bill, of how I met him, and one way his work and kindness impacted my life

    Coalgebraic semantics for parallel derivation strategies in logic programming

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    Logic programming, a class of programming languages based on first-order logic, provides simple and efficient tools for goal-oriented proof-search. Logic programming supports recursive computations, and some logic programs resemble the inductive or coinductive definitions written in functional programming languages. In this paper, we give a coalgebraic semantics to logic programming. We show that ground logic programs can be modelled by either P f P f -coalgebras or P f List-coalgebras on Set. We analyse different kinds of derivation strategies and derivation trees (proof-trees, SLD-trees, and-or parallel trees) used in logic programming, and show how they can be modelled coalgebraically.</p
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