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Proof-relevant Horn Clauses for Dependent Type Inference and Term Synthesis

机译:相关类型推断和术语合成的与证明相关的Horn子句

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First-order resolution has been used for type inference for many years, including in Hindley-Milner type inference, type-classes, and constrained data types. Dependent types are a new trend in functional languages. In this paper, we show that proof-relevant first-order resolution can play an important role in automating type inference and term synthesis for dependently typed languages. We propose a calculus that translates type inference and term synthesis problems in a dependently typed language to a logic program and a goal in the proof-relevant first-order Horn clause logic. The computed answer substitution and proof term then provide a solution to the given type inference and term synthesis problem. We prove the decidability and soundness of our method.
机译:多年来,一阶解析已用于类型推断,包括在Hindley-Milner类型推断,类型类和受约束的数据类型中。依赖类型是功能语言中的新趋势。在本文中,我们证明了与证明相关的一阶解析可以在依赖类型语言的类型推断和术语合成自动化中发挥重要作用。我们提出一种演算,该演算将依赖类型的语言中的类型推断和术语综合问题转换为逻辑程序,并证明与证明相关的一阶Horn子句逻辑中的目标。然后,计算出的答案替换和证明项将为给定的类型推断和项综合问题提供解决方案。我们证明了我们方法的可判定性和可靠性。

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