sk -组合子树的类型推断、生成和归一化之间的协同作用

Paul Tarau
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引用次数: 0

摘要

S和K组合子表达式形成了众所周知的微积分的图灵完全子集。使用Prolog作为元语言,我们为sk -组合子树指定了求值、类型推断和组合生成算法。在这个过程中,我们揭示了它们的结构和分布的有趣方面。我们研究了大小有限的sk表达式中类型良好的术语的比例,以及大小小于其简单类型大小的术语的类型定向生成。我们还引入了不可类型化术语的良好类型边界,并利用良好类型术语是可规范化的这一事实,为不可类型化术语设计了一个简化算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Synergies between Type Inference, Generation and Normalization of SK-Combinator Trees
The S and K combinator expressions form a well-known Turing-complete subset of the lambda calculus. Using Prolog as a meta-language, we specify evaluation, type inference and combinatorial generation algorithms for SK-combinator trees. In the process, we unravel properties shedding new light on interesting aspects of their structure and distribution. We study the proportion of well-typed terms among size-limited SK-expressions as well as the type-directed generation of terms of sizes smaller than the size of their simple types. We also introduce the well-typed frontier of an untypable term and we use it to design a simplification algorithm for untypable terms taking advantage of the fact that well-typed terms are normalizable.
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