Journals / Mathematical and Computational Applications / 2002 / Cilt: 7 - Sayı: 3

A template based graph reduction system based on combinators

Pages
253–262
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The test results show that pur approach increases the efficiency of super-combinators algorithms,

📌 3 Key Takeaways

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Objective & Hypothesis:Graph reduction is one of the important evaluation strategy for lazy functional programming.
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Key Findings & Data:A combinator is a function that contains no free variables.
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Conclusion & Impact:The test results show that pur approach increases the efficiency of super-combinators algorithms,
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Graph reduction is one of the important evaluation strategy for lazy functional programming. A combinator is a function that contains no free variables. The idea is based on the fact that, all of the variables in a program can be removed by transforming it into a sequence of combiriators which would be drawn from a small pre-defined (fixed) set of combinators (SKI), or which would be drawn from an unlimited number of non-pre-defined set of dynamic super-combinators (SC). We are suggesting a template based algorithm which reduces the stored graph structure of the super-combinators. We can define any produced super-combinators by using templates and use them to perform reduction on the graph. The template based algorithm could be extended and any produced super-combinators can be defined with a predefined template list. The test results show that pur approach increases the efficiency of super-combinators algorithms,

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Cite This Article

ÇAVUŞOĞLU, A., GÖKTAŞ, H. H., VARDAL, N. (2002). A template based graph reduction system based on combinators. Mathematical and Computational Applications, Cilt: 7 - Sayı: 3, 253–262. https://ajindex.com/articles/280168

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