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Typed Self-Interpretation by Pattern Matching

机译:通过模式匹配输入自我解释

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摘要

Self-interpreters can be roughly divided into two sorts: self-recog-nisers that recover the input program from a canonical representation, and self-enactors that execute the input program. Major progress for statically-typed languages was achieved in 2009 by Rendel, Ostermann, and Hofer who presented the first typed self-recogniser that allows representations of different terms to have different types. A key feature of their type system is a type:type rule that renders the kind system of their language inconsistent. In this paper we present the first statically-typed language that not only allows representations of different terms to have different types, and supports a self-recogniser, but also supports a self-enactor. Our language is a factorisation calculus in the style of Jay and Given-Wilson, a combinatory calculus with a factorisation operator that is powerful enough to support the pattern-matching functions necessary for a self-interpreter. This allows us to avoid a typertype rule. Indeed, the types of System F are sufficient. We have implemented our approach and our experiments support the theory.
机译:自我解释器可以大致分为两种:从标准表示形式恢复输入程序的自我识别程序,以及执行输入程序的自我执行程序。 Rendel,Ostermann和Hofer于2009年取得了静态类型语言的重大进展,他们提出了首个类型化自我识别器,该识别器允许不同术语的表示具有不同类型。他们的类型系统的关键特征是type:type规则,该规则使他们的语言的类型系统不一致。在本文中,我们介绍了第一种静态类型的语言,该语言不仅允许不同术语的表示形式具有不同的类型,并支持自识别器,而且还支持自执行器。我们的语言是Jay和Given-Wilson风格的因式分解演算,它是具有因式分解运算符的组合演算,其功能强大到足以支持自解释器所需的模式匹配功能。这使我们避免了typertype规则。实际上,系统F的类型就足够了。我们已经实现了我们的方法,我们的实验支持了这一理论。

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