2004
DOI: 10.1145/963778.963784
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Offline partial evaluation can be as accurate as online partial evaluation

Abstract: We show that the accuracy of online partial evaluation, or polyvariant specialization based on constant propagation, can be simulated by offline partial evaluation using a maximally polyvariant binding-time analysis. We point out that, while their accuracy is the same, online partial evaluation offers better opportunities for powerful generalization strategies. Our results are presented using a flowchart language with recursive procedures.

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Cited by 16 publications
(12 citation statements)
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References 41 publications
(60 reference statements)
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“…[3,4,14,16,17]), which should make our results easily comparable and accessible. Throughout this paper, we assume that readers are familiar with the basics of partial evaluation, e.g., as presented by Jones et al [18,Part II].…”
Section: Introductionmentioning
confidence: 91%
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“…[3,4,14,16,17]), which should make our results easily comparable and accessible. Throughout this paper, we assume that readers are familiar with the basics of partial evaluation, e.g., as presented by Jones et al [18,Part II].…”
Section: Introductionmentioning
confidence: 91%
“…We use two specializers in our experiments, and these represent typical offline and online partial evaluators for flowchart languages [14,[16][17][18]. 4 1. For an independent comparison, we use the classic offline partial evaluator mix by Gomard and Jones [16].…”
Section: Experimental Assessmentmentioning
confidence: 99%
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“…While offline partial evaluators are usually faster, online ones produce more accurate results (though, from a theoretical point of view, they are equally powerful [3]). Partial evaluators based on the CPD scheme have traditionally followed the online approach.…”
Section: Introductionmentioning
confidence: 99%
“…-The offline approach is in principle less precise (see, however, [6]) as it has to make decisions before the actual static values are known. -The offline approach leads to simpler specialisers, thus making self-application easier and leading to more efficient specialisation.…”
Section: Introductionmentioning
confidence: 99%