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Published in:
2008 | OriginalPaper | Chapter
Trace Analysis for Predicting the Effectiveness of Partial Evaluation
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The main goal of
partial evaluation
[1] is program specialization. Essentially, given a program and
part
of its input data|the so called
static
data|a partial evaluator returns a new, residual program which is specialized for the given data. An appropriate
residual
program for executing the remaining computations|those that depend on the so called
dynamic
data|is thus the output of the partial evaluator. Despite the fact that the main goal of partial evaluation is improving program efficiency (i.e., producing faster programs), there are very few approaches devoted to formally analyze the effects of partial evaluation, either
a priori
(prediction) or
a posteriori
. Recent approaches (e.g., [2,3]) have considered
experimental
frameworks for estimating the best
division
(roughly speaking, a classification of program parameters into static or dynamic), so that the optimal choice is followed when specializing the source program.