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arXiv 2301.09802cs.LO
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余归纳类型的归纳推理

Inductive Reasoning for Coinductive Types

Alexander Bagnall, Gordon Stewart, Anindya Banerjee

AI总结:

本文提出 AlgCo 框架,利用代数完全偏序和稠密集合上的原始递归,实现对 conats、流等余归纳类型的归纳推理,并在 Coq 中验证了筛法、正则表达式库和概率采样语义。

摘要:

我们提出了 AlgCo(Algebraic Coinductives,代数余归纳),这是一个实用的框架,用于对常用的余归纳类型(如 conats、流和具有有限分支因子的无限树)进行归纳推理。其核心思想是利用领域理论中的代数完全偏序概念,通过对元素“稠密”集合的原始递归来定义余归纳类型上的连续操作,从而通过简单的归纳证明,为代数余归纳的推理提供一种便捷的策略。我们在 Coq 中实现了 AlgCo 框架,并通过验证 Eratosthenes 筛法的流变体、基于形式语言的余归纳 trie 编码的正则表达式库,以及随机比特模型下离散概率分布上余归纳采样过程的期望值语义,展示了其强大能力。

英文摘要:

We present AlgCo (Algebraic Coinductives), a practical framework for inductive reasoning over commonly used coinductive types such as conats, streams, and infinitary trees with finite branching factor. The key idea is to exploit the notion of algebraic complete partial order from domain theory to define continuous operations over coinductive types via primitive recursion on ``dense'' collections of their elements, enabling a convenient strategy for reasoning about algebraic coinductives by straightforward proofs by induction. We implement the AlgCo framework in Coq and demonstrate its power by verifying a stream variant of the sieve of Eratosthenes, a regular expression library based on coinductive trie encodings of formal languages, and expected value semantics for coinductive sampling processes over discrete probability distributions in the random bit model.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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