Software fault prediction using Whale algorithm with genetics algorithm. (15th December 2020)

• Record Type: Journal Article
• Authors: Alsghaier, Hiba; Akour, Mohammed
• Is Part Of: Software, practice & experience. Volume 51:Number 5(2021)
• Page Start: 1121
• Page End: 1146
• Publication Date: 2020-12-15
• Subjects: fault prediction -- genetics algorithm -- machine learning -- optimization algorithms -- Whale algorithm; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2941
• Languages: English
• ISSNs: 0038-0644

Abstract

Abstract: Software fault prediction became an essential research area in the last few years, there are many prediction and optimization techniques that have been developed for fault prediction. In this paper, an approach is developed by integrating genetics algorithm with support vector machine (SVM) classifier and Whale optimization algorithm for software fault prediction. The developed approach is applied to 24 datasets (12‐NASA MDP and 12‐Java open‐source projects), where NASA MDP is considered as a large‐scale dataset, and Java open source projects are considered as a small‐scale dataset. Results indicate that integrating Genetics algorithm with SVM and Whale algorithm improves the performance of the software fault prediction process when it is applied to large‐scale and small‐scale datasets and overcome the limitations that appeared in the previous studies.