A comparative analysis of soft computing techniques in software fault prediction model development

被引:9
|
作者
Sharma D. [1 ]
Chandra P. [1 ]
机构
[1] University School of Information Communication and Technology, Guru Gobind Singh Indraprastha University, Dwarka, 110078, Delhi
关键词
Evolutionary computing; Fuzzy logic; Machine learning; Neural network; Soft computing; Software fault prediction; Swarm intelligence;
D O I
10.1007/s41870-018-0211-3
中图分类号
学科分类号
摘要
In the process of software development, software fault prediction is a useful practice to ensure reliable and high quality software products. It plays a vital role in the process of software quality assurance. A high quality software product contains minimum number of faults and failures. Software fault prediction examines the vulnerability of software product towards faults. In this paper, a comparative analysis of various soft computing approaches in terms of the process of software fault prediction is considered. In addition, an analysis of various pros and cons of soft computing techniques in terms of software fault prediction process is also mentioned. The conclusive results show that the soft computing approach has the propensity to identify faults in the process of software development. © 2018, Bharati Vidyapeeth's Institute of Computer Applications and Management.
引用
收藏
页码:37 / 46
页数:9
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