SPBC: A self-paced learning model for bug classification from historical repositories of open-source software

作者：

Highlights：

• A novel back traceable self paced learning algorithm for bug classification.

• Data insertion in self paced manner achieves 99% precision, on average.

• Data independent back traceable matrix helps in acquiring stability of performance.

• Independent of the data sets and keeps the performance intact.

摘要

•A novel back traceable self paced learning algorithm for bug classification.•Data insertion in self paced manner achieves 99% precision, on average.•Data independent back traceable matrix helps in acquiring stability of performance.•Independent of the data sets and keeps the performance intact.

论文关键词：Bug triaging,Defect localization,Self-paced learning,Bug report analysis,Bug classification

论文评审过程：Received 18 June 2019, Revised 28 July 2020, Accepted 29 July 2020, Available online 19 August 2020, Version of Record 10 February 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113808