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Memoized Pull-Tabbing for Functional Logic Programming

Authors: Michael Hanus; Finn Teegen;

Memoized Pull-Tabbing for Functional Logic Programming

Abstract

Pull-tabbing is an evaluation technique for functional logic programs which computes all non-deterministic results in a single graph structure. Pull-tab steps are local graph transformations to move non-deterministic choices towards the root of an expression. Pull-tabbing is independent of a search strategy so that different strategies (depth-first, breadth-first, parallel) can be used to extract the results of a computation. It has been used to compile functional logic languages into imperative or purely functional target languages. Pull-tab steps might duplicate choices in case of shared subexpressions. This could result in a dramatic increase of execution time compared to a backtracking implementation. In this paper we propose a refinement which avoids this efficiency problem while keeping all the good properties of pull-tabbing. We evaluate a first implementation of this improved technique in the Julia programming language.

Part of WFLP 2020 pre-proceedings

Keywords

FOS: Computer and information sciences, Computer Science - Programming Languages, Programming Languages (cs.PL)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green