Effort-aware just-in-time defect identification in practice: a case study at Alibaba
Abstract
Effort-aware Just-in-Time (JIT) defect identification aims at identifying defect-introducing changes just-in-time with limited code inspection effort. Such identification has two benefits compared with traditional module-level defect identification, i.e., identifying defects in a more cost-effective and efficient manner. Recently, researchers have proposed various effort-aware JIT defect identification approaches, including supervised (e.g., CBS+, OneWay) and unsupervised approaches (e.g., LT and Code Churn). The comparison of the effectiveness between such supervised and unsupervised approaches has attracted a large amount of research interest. However, the effectiveness of the recently proposed approaches and the comparison among them have never been investigated in an industrial setting.
BibTeX
@inproceedings{Yan-al:FSE20,
author = {Meng Yan and
Xin Xia and
Yuanrui Fan and
David Lo and
Ahmed E. Hassan and
Xindong Zhang},
title = {Effort-aware just-in-time defect identification in practice: a case study at Alibaba},
booktitle = {{ESEC/SIGSOFT} {FSE}},
pages = {1308--1319},
publisher = {{ACM}},
year = {2020},
}