Genetically Programmed Pattern Matching for Overlapping Patterns

2006 International Conference on Computer Engineering and Systems Pub Date : 2006-11-01 DOI:10.1109/ICCES.2006.320482

N. Nedjah, L. de Macedo Mourelle

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Abstract

Pattern matching is a fundamental feature in many applications such as functional programming, logic programming, theorem proving, term rewriting and rule-based expert systems. Usually, patterns size is not constrained and ambiguous patterns are allowed. This generality leads to a clear and concise programming style. However, it yields challenging problems in compiling of such programming languages. Generally, patterns are pre-processed into a deterministic finite automaton. With ambiguous or overlapping patterns a subject term may be an instance of more than one pattern. In this case, pattern matching order in lazy evaluation affects the size of the matching automaton and the matching time. Furthermore, it may even affect the termination properties of term evaluations. In this paper, we engineer good traversal orders that allow one to design an efficient adaptive pattern-matchers that visit necessary positions only. We do so using genetic programming to evolve the most adequate traversal order given the set of allowed patterns. Hence, we improve time and space requirements of pattern-matching as well as termination properties of term evaluation

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重叠模式的遗传程序模式匹配

模式匹配是函数式编程、逻辑编程、定理证明、术语重写和基于规则的专家系统等许多应用程序的基本特征。通常，模式大小不受限制，并且允许使用模糊模式。这种通用性导致了一种清晰而简洁的编程风格。然而，它在编译这些编程语言时产生了具有挑战性的问题。通常，模式被预处理成确定性有限自动机。对于模棱两可或重叠的模式，主题词可以是一个以上模式的实例。在这种情况下，惰性求值中的模式匹配顺序会影响匹配自动机的大小和匹配时间。此外，它甚至可能影响项求值的终止属性。在本文中，我们设计了良好的遍历顺序，允许设计一个有效的自适应模式匹配器，只访问必要的位置。我们使用遗传编程来进化最合适的遍历顺序，给定允许的模式集。因此，我们改进了模式匹配的时间和空间要求以及项求值的终止特性

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2006 International Conference on Computer Engineering and Systems

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