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The Power of Parameterization in Coinductive Proof

机译:归纳证明中参数化的力量

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摘要

Coinduction is one of the most basic concepts in computer science. It is therefore surprising that the commonly-known lattice-theoretic accounts of the principles underlying coinductive proofs are lacking in two key respects: they do not support compositional reasoning (i.e., breaking proofs into separate pieces that can be developed in isolation), and they do not support incremental reasoning (i.e., developing proofs interactively by starting from the goal and generalizing the coinduction hypothesis repeatedly as necessary). In this paper, we show how to support coinductive proofs that are both compositional and incremental, using a dead simple construction we call the parameterized greatest fixed point. The basic idea is to parameterize the greatest fixed point of interest over the accumulated knowledge of 'the proof so far'. While this idea has been proposed before, by Winskel in 1989 and by Moss in 2001, neither of the previous accounts suggests its general applicability to improving the state of the art in interactive coinductive proof. In addition to presenting the lattice-theoretic foundations of parameterized coinduction, demonstrating its utility on representative examples, and studying its composition with 'up-to' techniques, we also explore its mechanization in proof assistants like Coq and Isabelle. Unlike traditional approaches to mechanizing coinduction (e.g., Coq's cofix), which employ syntactic 'guardedness checking', parameterized coinduction offers a semantic account of guardedness. This leads to faster and more robust proof development, as we demonstrate using our new Coq library, Paco.
机译:共生是计算机科学中最基本的概念之一。因此,令人惊讶的是,在以下两个主要方面缺乏对共归证明所基于的原理的众所周知的晶格理论解释:它们不支持成分推理(即,将证明分解为可以单独开发的独立部分),并且不支持增量推理(即通过从目标开始并在必要时反复概括共归假设来交互式地开发证明)。在本文中,我们展示了如何使用固定的简单构造(称为参数化最大不动点)来支持组成和增量的共导证明。基本思想是根据“到目前为止的证据”的累积知识,对最大兴趣点进行参数化。尽管这个想法是由Winskel于1989年和Moss于2001年提出的,但先前的记载均未表明其在交互式共归证明中改善现有技术水平的普遍适用性。除了提供参数化共导的格架理论基础,在代表性示例上证明其效用以及使用“最新”技术研究其组成外,我们还通过Coq和Isabelle等证明助手来探索其机械化。与采用句法``防护检查''的机械化共生的传统方法(例如Coq的cofix)不同,参数化共生提供了防护的语义说明。正如我们使用新的Coq库Paco所演示的那样,这将导致更快,更可靠的证明开发。

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