一句话：提出 AID，将 GenderMag 自动化以检测 OSS 项目页面中的性别包容性缺陷，并在 20 个 GitHub 项目上验证。
开源软件及其工具链可能隐含“包容性缺陷”，使特定贡献者群体处于不利地位。为了解现状，作者调查了 266 名 OSS 开发者，发现 77% 未采用任何包容性实践，92% 表示缺乏具体可用的资源。为此，论文提出 AID：一个将 GenderMag 方法自动化的工具，用于系统检测软件中的性别包容性缺陷。作者在 20 个 GitHub 项目上评估 AID，得到精确率 0.69、召回率 0.92、F 值 0.79，并且还发现了人类 GenderMag 团队遗漏的部分包容性缺陷。结果表明，自动化方法可有效补充人工审查。
The tools and infrastructure used in tech, including Open Source Software (OSS), can embed "inclusivity bugs"- features that disproportionately disadvantage particular groups of contributors. To see whether OSS developers have existing practices to ward off such bugs, we surveyed 266 OSS developers. Our results show that a majority (77%) of developers do not use any inclusivity practices, and 92% of respondents cited a lack of concrete resources to enable them to do so. To help fill this gap, this paper introduces AID, a tool that automates the GenderMag method to systematically find gender-inclusivity bugs in software. We then present the results of the tool's evaluation on 20 GitHub projects. The tool achieved precision of 0.69, recall of 0.92, an F-measure of 0.79 and even captured some inclusivity bugs that human GenderMag teams missed.
@inproceedings{ChatterjeeGSEMB21,
title = {AID: An Automated Detector for Gender-Inclusivity Bugs in OSS Project Pages},
author = {Amreeta Chatterjee and Mariam Guizani and Catherine Stevens and Jillian Emard and Mary Evelyn May and Margaret Burnett and Iftekhar Ahmed},
booktitle = {ICSE},
year = {2021},
doi = {10.1109/icse43902.2021.00128}
}