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Algorithm Recognition based on Demand-Driven Dataflow Analysis

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Abstract

Algorithm recognition is an important problem in program analysis, optimization, and more particularly program comprehension. Basically, one would like to submit a piece of code, and get an answer like " Lines 10 to 23 are an implementation of Gauss-Jordan elimination ". Existing approaches often perform a bottom-up recognition, using a database describing many implementation variations of a given algorithm, in a format making them difficult to maintain. In this paper, we present a new method to recognize algorithm templates in a program. We perform a top-down recognition, stopping at template variables and thus limiting the need for many program variations. The code to analyze is given in SSA form, and the-functions are computed on-demand, when computation is possible, along the candidate slices.
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Dates and versions

ensl-01663748 , version 1 (14-12-2017)

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  • HAL Id : ensl-01663748 , version 1

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Christophe Alias, Denis Barthou. Algorithm Recognition based on Demand-Driven Dataflow Analysis. 10th Working Conference on Reverse Engineering (WCRE 2003), Nov 2003, Victoria, Canada. ⟨ensl-01663748⟩
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