模一元元理论

Benjamin Delaware, Steven Keuchel, T. Schrijvers, B. C. D. S. Oliveira
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引用次数: 32

摘要

本文提出了一个具有效果语言的模块化机械化元理论框架——3MT。使用3MT,单个语言特征及其对应的定义——语义函数、定理陈述和证明——可以单独构建,然后再利用,以完全机械化的元理论创建不同的语言。3MT结合了模块化数据类型和单元体,以每个特性为基础定义具有效果的指示语义,而不固定特定的效果集或语言结构。指称语义的类型可靠性证明的一个公认问题是,它们在添加新效果方面非常脆弱。一种语言的类型健全性声明密切依赖于它所使用的效果,这使得实现模块化特别具有挑战性。3MT通过将这些定理拆分为两个独立且可重用的部分来解决这个长期存在的问题:一个特征定理捕获由单个特征的语义函数产生的表意的良好类型,仅针对所使用的效果,另一个效果定理将表意的良好类型适应于固定的超集效果。特定语言的类型稳健性证明只是将这些定理的特征和它们的效果组合在一起。为了建立这两个定理,3MT使用了两个关键的推理技术:模归纳法和关于效应的代数定律。几个有效的语言特性(包括引用和错误)说明了3MT的功能。一个案例研究重用这些特性,为28种语言构建完全机械化的定义和证明,包括几个具有效果的mini-ML版本。
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Modular monadic meta-theory
This paper presents 3MT, a framework for modular mechanized meta-theory of languages with effects. Using 3MT, individual language features and their corresponding definitions -- semantic functions, theorem statements and proofs-- can be built separately and then reused to create different languages with fully mechanized meta-theory. 3MT combines modular datatypes and monads to define denotational semantics with effects on a per-feature basis, without fixing the particular set of effects or language constructs. One well-established problem with type soundness proofs for denotational semantics is that they are notoriously brittle with respect to the addition of new effects. The statement of type soundness for a language depends intimately on the effects it uses, making it particularly challenging to achieve modularity. 3MT solves this long-standing problem by splitting these theorems into two separate and reusable parts: a feature theorem that captures the well-typing of denotations produced by the semantic function of an individual feature with respect to only the effects used, and an effect theorem that adapts well-typings of denotations to a fixed superset of effects. The proof of type soundness for a particular language simply combines these theorems for its features and the combination of their effects. To establish both theorems, 3MT uses two key reasoning techniques: modular induction and algebraic laws about effects. Several effectful language features, including references and errors, illustrate the capabilities of 3MT. A case study reuses these features to build fully mechanized definitions and proofs for 28 languages, including several versions of mini-ML with effects.
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