元理论a点菜

Benjamin Delaware, Bruno C. d. S. Oliveira, Tom Schrijvers
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引用次数: 63

摘要

在证明助手中形式化元理论或关于编程语言的证明有许多众所周知的好处。不幸的是,机械化证明所涉及的大量努力阻止了它成为标准做法。在构建新语言或扩展现有语言时,可以通过重用尽可能多的现有机械化形式化来分摊此成本。实现重用的一个重要挑战是,这些形式化中使用的归纳定义和证明对扩展是封闭的。这迫使语言设计者以一种特殊的方式剪切和粘贴现有的定义和证明,并花费大量的精力来修补结果。本文的主要贡献是利用对折叠全称性质的一种新的重新解释,发展了一种可扩展的丘奇编码的归纳法。这些编码为Coq中形式化的框架提供了基础,该框架使用类型类来自动组合来自模块化组件的证明。该框架通过组合模块化归纳定义和证明,使元理论形式化的重用成为一种更加结构化的方法。几个有趣的语言特性,包括绑定器和一般递归,说明了我们框架的功能。我们重用这些特性来为许多语言(包括一个mini-ML版本)构建完全机械化的定义和证明。有界归纳法支持对非归纳语义函数的性质进行证明,而中介类型类支持对功能更丰富的语言进行证明。
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Meta-theory à la carte
Formalizing meta-theory, or proofs about programming languages, in a proof assistant has many well-known benefits. Unfortunately, the considerable effort involved in mechanizing proofs has prevented it from becoming standard practice. This cost can be amortized by reusing as much of existing mechanized formalizations as possible when building a new language or extending an existing one. One important challenge in achieving reuse is that the inductive definitions and proofs used in these formalizations are closed to extension. This forces language designers to cut and paste existing definitions and proofs in an ad-hoc manner and to expend considerable effort to patch up the results. The key contribution of this paper is the development of an induction technique for extensible Church encodings using a novel reinterpretation of the universal property of folds. These encodings provide the foundation for a framework, formalized in Coq, which uses type classes to automate the composition of proofs from modular components. This framework enables a more structured approach to the reuse of meta-theory formalizations through the composition of modular inductive definitions and proofs. Several interesting language features, including binders and general recursion, illustrate the capabilities of our framework. We reuse these features to build fully mechanized definitions and proofs for a number of languages, including a version of mini-ML. Bounded induction enables proofs of properties for non-inductive semantic functions, and mediating type classes enable proof adaptation for more feature-rich languages.
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Session details: Verified systems Session details: Semantic models 2 Session details: Program analysis 3 Session details: Program analysis 1 Session details: Type system design
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