文章基本信息

标题：Comparative Performance Analysis of Machine Learning Techniques for Software Bug Detection
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作者：Saiqa Aleem ; Luiz Fernando Capretz ; Faheem Ahmed 等
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2015
卷号：5
期号：1
页码：71-79
DOI：10.5121/csit.2015.50108
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Machine learning techniques can be used to analyse data from different perspectives and enabledevelopers to retrieve useful information. Machine learning techniques are proven to be usefulin terms of software bug prediction. In this paper, a comparative performance analysis ofdifferent machine learning techniques is explored for software bug prediction on publicavailable data sets. Results showed most of the machine learning methods performed well onsoftware bug datasets.
关键词：Machine Learning Methods; Software Bug Detection; Predictive Analytics.