一句话：通过访谈与问卷调研从业者对自动注释生成的期望，并与 2010–2020 年顶会研究现状对比，指出研究应努力的方向。
良好的注释是软件项目的重要资产，可帮助开发者理解与维护代码；但实践中注释常缺失或与源码不一致，开发者不得不花费大量时间阅读缺乏注释的程序。近年来研究者提出多种自动生成代码注释的技术，然而这些技术能否真正缓解注释问题、从业者是否认可这条研究路线仍不明确。为填补这一空白，本文开展了一项实证研究：通过访谈与问卷调查收集从业者对代码注释生成研究的期望，同时对 2010 至 2020 年间发表于顶级会议与期刊的代码注释生成技术论文进行文献综述，并将从业者的实际需求与当前研究现状进行系统对比。基于该对比，作者指出了研究者需要重点投入、以开发出真正对从业者有价值的注释生成技术的方向。
Good comments are invaluable assets to software projects, as they help developers understand and maintain projects. However, due to some poor commenting practices, comments are often missing or inconsistent with the source code. Software engineering practitioners often spend a significant amount of time and effort reading and understanding programs without or with poor comments. To counter this, researchers have proposed various techniques to automatically generate code comments in recent years, which can not only save developers time writing comments but also help them better understand existing software projects. However, it is unclear whether these techniques can alleviate comment issues and whether practitioners appreciate this line of research. To fill this gap, we performed an empirical study by interviewing and surveying practitioners about their expectations of research in code comment generation. We then compared what practitioners need and the current state-of-the-art research by performing a literature review of papers on code comment generation techniques published in the premier publication venues from 2010 to 2020. From this comparison, we highlighted the directions where researchers need to put effort to develop comment generation techniques that matter to practitioners.
@inproceedings{paperbot6903,
title = {Practitioners' expectations on automated code comment generation},
author = {Xing Hu and Xin Xia and David Lo and Zhiyuan Wan and Qiuyuan Chen and Thomas Zimmermann},
booktitle = {ICSE},
year = {2022},
doi = {10.1145/3510003.3510152}
}