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Folding variant narrowing and optimal variant termination

机译:折叠变体变窄和最佳变体终止

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Automated reasoning modulo an equational theory ε is a fundamental technique in many applications. If ε can be split as a disjoint union E ∪ Ax in such a way that E is confluent, terminating, sort-decreasing, and coherent modulo a set of equational axioms Ax, narrowing with E modulo Ax provides a complete ε-unification algorithm. However, except for the hopelessly inefficient case of full narrowing, little seems to be known about effective narrowing strategies in the general modulo case beyond the quite depressing observation that basic narrowing is incomplete modulo AC. Narrowing with equations E modulo axioms Ax can be turned into a practical automated reasoning technique by systematically exploiting the notion of E, Ax-variants of a term. After reviewing such a notion, originally proposed by Comon-Lundh and Delaune, and giving various necessary and/or sufficient conditions for it, we explain how narrowing strategies can be used to obtain narrowing algorithms modulo axioms that are: (i) variant-complete (generate a complete set of variants for any input term), (ii) minimal (such a set does not have redundant variants), and (iii) are optimally variant-terminating (the strategy will terminate for an input term t iff t has a finite complete set of variants). We define a strategy called folding variant narrowing that satisfies above properties (i)-(iii); in particular, when E ∪ Ax has the finite variant property, that is, when any term t has a finite complete set of variants, this strategy terminates on any input term and provides a finitary E ∪ Ax-unification algorithm. We also explain how folding variant narrowing has a number of interesting applications in areas such as unification theory, cryptographic protocol verification, and proofs of termination, confluence and coherence of a set of rewrite rules R modulo an equational theory E.
机译:在许多应用中,以方程理论ε为模的自动推理是一项基本技术。如果将ε分解为不相交的并集E∪Ax,以使E收敛,终止,减少排序和相干模,则一组方程式公理Ax随E模Ax变窄即可提供完整的ε统一算法。但是,除了完全缩小的无希望的低效率情况外,对于一般的模数情况,除了基本的缩小不是完全模数AC的令人沮丧的观察之外,对于有效的缩小策略似乎知之甚少。通过系统地利用术语E的Ax变量的概念,可以将方程式E的模数公理Ax缩小为实用的自动推理技术。在回顾了最初由Comon-Lundh和Delaune提出的这种概念,并给出了各种必要和/或充分的条件之后,我们解释了如何使用缩小策略来获得模数公理的缩小算法,这些算法是:(i)变体完全(为任何输入项生成完整的变体集),(ii)最小(这样的集合不具有多余的变体),并且(iii)最优地终止变体(该策略将在输入条件为t时终止)有限的完整变体集)。我们定义了一种满足上述特性(i)-(iii)的称为折叠变体变窄的策略;特别地,当E∪Ax具有有限的变体性质时,即当任意项t具有有限的完整变体集时,该策略在任何输入项上终止,并提供最终的E∪Ax统一算法。我们还解释了折叠变体变窄如何在诸如统一理论,密码协议验证以及以等式理论E为模的一组重写规则R的终止,融合和连贯性证明方面具有许多有趣的应用。

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