Linear and non-linear heterogeneous ensemble methods to predict the number of faults in software systems

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• 作者：Santosh Singh Rathore ^{sunnydec@iitr.ac.in} ; Sandeep Kumar ; ^{sgargfec@iitr.ac.in}
• 关键词：Software fault prediction ; Ensemble methods ; Heterogeneous ensemble ; Prediction of number of faults
• 刊名：Knowledge-Based Systems
• 出版年：2017
• 出版时间：1 March 2017
• 年：2017
• 卷：119
• 期：Complete
• 页码：232-256
• 全文大小：4074 K
• 卷排序：119

文摘

This paper expands the use of ensemble methods for the prediction of number of faults unlikely the earlier works on ensemble methods that focused on predicting software modules as faulty or non-faulty. This paper investigates the usage of both heterogeneous ensemble methods as well as homogeneous ensemble methods for the prediction of number of faults. We present two linear combination rules and two non-linear combination rules for combining the outputs of the base learners in the ensemble. In addition, we assess the performance of ensemble methods under two different scenarios, intra-release prediction and inter-releases prediction. The experiments are performed over five open-source software systems with their fifteen releases, collected from the PROMISE data repository.