Volume 9 Number 5 (May 2014)
Home > Archive > 2014 > Volume 9 Number 5 (May 2014) >
JSW 2014 Vol.9(5): 1324-1333 ISSN: 1796-217X
doi: 10.4304/jsw.9.5.1324-1333

Metaheuristic Optimization based Feature Selection for Software Defect Prediction

Romi Satria Wahono1, 2, Nanna Suryana1, Sabrina Ahmad1
1Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka
2Graduate School of Computer Science, Dian Nuswantoro University, Semarang, Indonesia


Abstract—Software defect prediction has been an important research topic in the software engineering field, especially to solve the inefficiency and ineffectiveness of existing industrial approach of software testing and reviews. The software defect prediction performance decreases significantly because the data set contains noisy attributes and class imbalance. Feature selection is generally used in machine learning when the learning task involves highdimensional and noisy attribute datasets. Most of the feature selection algorithms, use local search throughout the entire process, consequently near-optimal to optimal solutions are quiet difficult to be achieved. Metaheuristic optimization can find a solution in the full search space and use a global search ability, significantly increasing the ability of finding high-quality solutions within a reasonable period of time. In this research, we propose the combination of metaheuristic optimization methods and bagging technique for improving the performance of the software defect prediction. Metaherustic optimization methods (genetic algorithm and particle swarm optimization) are applied to deal with the feature selection, and bagging technique is employed to deal with the class imbalance problem. Results have indicated that the proposed methods makes an impressive improvement in prediction performance for most classifiers. Based on the comparison result, we conclude that there is no significant difference between particle swarm optimization and genetic algorithm when used as feature selection for most classifiers in software defect prediction.

Index Terms—software defect prediction, feature selection, genetic algorithm, particle swarm optimization, bagging technique

[PDF]

Cite: Romi Satria Wahono, Nanna Suryana, Sabrina Ahmad, "Metaheuristic Optimization based Feature Selection for Software Defect Prediction," Journal of Software vol. 9, no. 5, pp. 1324-1333, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
  • Dec 06, 2019 News!

    Vol 14, No 1- Vol 14, No 4 has been indexed by EI (Inspec)   [Click]

  • Nov 18, 2019 News!

    Papers published in JSW Vol 14, No 1- Vol 14 No 10 have been indexed by DBLP     [Click]

  • Dec 06, 2019 News!

     Vol 13, No 10- Vol 13, No 12 has been indexed by EI (Inspec)   [Click]

  • Aug 01, 2018 News!

    [CFP] 2020 the annual meeting of JSW Editorial Board, ICCSM 2020, will be held in Rome, Italy, July 17-19, 2020   [Click]

  • Jun 25, 2019 News!

    Vol.13, No.9 has been indexed by EI (Inspec).   [Click]