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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
computer science
A Cooperative Parallel Search-Based Software Engineering Approach for Code-Smells Detection
IEEE Transactions on Software Engineering, Volume 40, No. 9, Article 2331057, Year 2014
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Description
We propose in this paper to consider code-smells detection as a distributed optimization problem. The idea is that different methods are combined in parallel during the optimization process to find a consensus regarding the detection of code-smells. To this end, we used Parallel Evolutionary algorithms (P-EA) where many evolutionary algorithms with different adaptations (fitness functions, solution representations, and change operators) are executed, in a parallel cooperative manner, to solve a common goal which is the detection of code-smells. An empirical evaluation to compare the implementation of our cooperative P-EA approach with random search, two single population-based approaches and two code-smells detection techniques that are not based on meta-heuristics search. The statistical analysis of the obtained results provides evidence to support the claim that cooperative P-EA is more efficient and effective than state of the art detection approaches based on a benchmark of nine large open source systems where more than 85 percent of precision and recall scores are obtained on a variety of eight different types of code-smells. © 2014 IEEE.
Authors & Co-Authors
Kessentini, Marouane
United States, Dearborn
University of Michigan-dearborn
Sahraoui, Houari A.
Canada, Montreal
University of Montreal
Bechikh, Slim
United States, Dearborn
University of Michigan-dearborn
Ouni, Ali
Canada, Montreal
University of Montreal
Statistics
Citations: 98
Authors: 4
Affiliations: 2
Identifiers
Doi:
10.1109/TSE.2014.2331057
ISSN:
00985589
Study Design
Cross Sectional Study
Study Approach
Quantitative