CRII: SHF: Improving the Retention of Newcomers in FLOSS Projects With Useful and Timely Code Reviews

CRII：SHF：通过有用且及时的代码审查来提高 FLOSS 项目中新人的保留率

• 批准号: 1850475
• 负责人: Amiangshu Bosu
• 金额: $ 17.5万
• 依托单位: Wayne State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-15 至 2022-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1850475&HistoricalAwards=false
• 关键词: CRII; SHF; Improving; Retention; Newcomers

Although popular Free / Libre Open Source Software (FLOSS) projects (e.g., Apache, Linux, and Android) attract plenty of motivated volunteers, most of these prospective joiners fail to become long-term contributors. According to the results of recent studies, one of the most common barriers reported by the newcomers is delayed or unfair feedback for their submitted code changes. This barrier often stems from a newcomer's struggle to identify suitable reviewers, who are experienced in the change areas and are capable of writing useful reviews. Since newcomers often have to wait 2-6 times longer than a long-term contributor to get reviews for their changes, they often become frustrated and abandon their on-boarding efforts. To address this issue, this project aims to build RevRanker, an automated model that can suggest reviewers who can provide timely and useful reviews.Toward this goal, this project will first build a theoretical understanding of useful code reviews in FLOSS projects using a mixed research method. This understanding will be then used to train and evaluate RevEval, an automated model to predict the usefulness of code reviews. Using the RevEval model as well as leveraging multiple historical dimensions of the files under review, RevRanker will be developed and evaluated. Finally, a plugin will be developed to integrate the RevRanker model with a popular code-review management system as well as to evaluate its effectiveness.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

虽然流行的自由/自由开源软件（FLOSS）项目（例如，Apache、Linux和Android）吸引了大量积极的志愿者，但这些潜在的加入者中的大多数都未能成为长期贡献者。 根据最近的研究结果，新来者报告的最常见的障碍之一是对他们提交的代码更改的延迟或不公平的反馈。这个障碍通常源于新人很难找到合适的评审员，他们在变更领域有经验，能够写出有用的评审。由于新人通常需要比长期贡献者等待2-6倍的时间才能获得对他们的更改的评论，他们经常会感到沮丧并放弃他们的入职努力。为了解决这个问题，本项目旨在构建RevRanker，这是一个自动化模型，可以推荐能够提供及时和有用的审查的审查者。为了实现这一目标，本项目将首先使用混合研究方法建立对FLOSS项目中有用代码审查的理论理解。这种理解将用于训练和评估RevEval，这是一个预测代码审查有用性的自动化模型。将使用RevEval模型并利用所审查文件的多个历史维度，开发和评估RevRanker。最后，将开发一个插件，将RevRanker模型与流行的代码审查管理系统集成，并评估其有效性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Code reviews in open source projects : how do gender biases affect participation and outcomes?

• DOI: 10.1007/s10664-023-10324-9
• 发表时间: 2022-09
• 期刊: Empirical Software Engineering
• 影响因子: 4.1
• 作者: Sayma Sultana;Asif Kamal Turzo;Amiangshu Bosu

What makes a code review useful to OpenDev developers? An empirical investigation

• DOI: 10.1007/s10664-023-10411-x
• 发表时间: 2023-02
• 期刊: Empirical Software Engineering
• 影响因子: 4.1
• 作者: Asif Kamal Turzo;Amiangshu Bosu

Using a balanced scorecard to identify opportunities to improve code review effectiveness: an industrial experience report

使用平衡计分卡来识别提高代码审查有效性的机会：行业经验报告

• DOI: 10.1007/s10664-021-10038-w
• 发表时间: 2021
• 期刊: Empirical Software Engineering
• 影响因子: 4.1
• 作者: Hasan, Masum;Iqbal, Anindya;Islam, Mohammad Rafid;Rahman, A.J.M. Imtiajur;Bosu, Amiangshu
• 通讯作者: Bosu, Amiangshu

Towards Automated Classification of Code Review Feedback to Support Analytics

• DOI: 10.1109/esem56168.2023.10304851
• 发表时间: 2023-07
• 期刊: 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)
• 作者: Asif Kamal Turzo;Fahim Faysal;Ovi Poddar;Jaydeb Sarker;Anindya Iqbal;Amiangshu Bosu

Towards Improving Code Review Effectiveness Through Task Automation

• DOI: 10.1145/3551349.3559565
• 发表时间: 2022-10
• 期刊: Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering
• 作者: Asif Kamal Turzo