Year: 2004
Type: conference-paper
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.
Authors: C. Alias, D. Barthou
Institution: Université de Versailles Saint-Quentin-en-Yvelines
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2101231351