一句话：该文讨论 JIT 缺陷预测的优势，并追问修复诱发变更是否随时间变化而成为移动目标。
摘要首先介绍变更级缺陷预测，也称 Just-In-Time（JIT）缺陷预测，并说明其相较模块级缺陷预测的优势：代码变更通常比类等模块更小，因此预测粒度更细，有助于定位检查范围；模块往往有多位作者，而一个变更只有一位作者，便于对 JIT 预测结果进行分诊；JIT 模型还能在变更产生过程中扫描变更，使问题能在设计决策仍记忆犹新时得到调查。标题进一步追问修复诱发变更是否为移动目标，即其相关模式或影响因素是否随时间变化。但摘要未给出具体方法、数据与结果，因此无法据此判断该问题是否通过实证研究、模型比较或时间序列分析来回答。
Change-level defect prediction [5], a.k.a., Just-In-Time (JIT) defect prediction [1], is an alternative to module-level defect prediction that offers several advantages. First, since code changes are often smaller than modules (e.g., classes), JIT predictions are made at a finer granularity, which localizes the inspection process. Second, while modules have a group of authors, changes have only one, which makes triaging JIT predictions easier. Finally, unlike module level prediction, JIT models can scan changes as they are being produced, which means that problems can be investigated while design decisions are still fresh in the developers' minds.
DOI 原文 ·
@inproceedings{paperbot4528,
title = {Are fix-inducing changes a moving target?},
author = {Shane McIntosh and Yasutaka Kamei},
booktitle = {ICSE},
year = {2018},
doi = {10.1145/3180155.3182514}
}