Abstract
In recent years many Open-Source Software (OSS) projects have adopted various automations to automate repetitive tasks, one category of automations adopted by OSS are so-called bots. In previous work, researchers have found that the adoption of bots helps open-source developers merge more pull requests and reduces the need
for communication between developers. The Apache Software Foundation (ASF) is a foundation that provides open-source software, and it supports the OSS projects that are a member of it. Projects that are a part of the ASF can choose to adopt the ASFBot, this bot automatically creates links between the JIRA issue tracker and pull requests (PRs) on GitHub. In this exploratory case study, we zoom in on the ASF ecosystem, and we seek to understand how the adoption of one specific bot (the ASFBot) impacts the discussions in the issue-trackers of these projects. In this study, we use the SmartShark dataset to investigate whether the ASFBot affects (i) human comments mentioning pull requests (PRs) and fixes in issue comments and (ii) the general human comment rate on issues. We apply a regression discontinuity design (RDD) on nine projects that are members of the ASF and which have been active both before
and after the adoption of the ASFBot. Our results indicate (i) a decrease in comments mentioning pull requests and fixes after the bot adoption and (ii) no effect in the number of human comments after the bot adoption. By taking a first step towards understanding how the adoption of ASFBot impacts the issue tracker of projects we can better understand the advantages that the infrastructure of a foundation like ASF provides, and how it affects the commenting behavior of developers in the issue-tracker.
for communication between developers. The Apache Software Foundation (ASF) is a foundation that provides open-source software, and it supports the OSS projects that are a member of it. Projects that are a part of the ASF can choose to adopt the ASFBot, this bot automatically creates links between the JIRA issue tracker and pull requests (PRs) on GitHub. In this exploratory case study, we zoom in on the ASF ecosystem, and we seek to understand how the adoption of one specific bot (the ASFBot) impacts the discussions in the issue-trackers of these projects. In this study, we use the SmartShark dataset to investigate whether the ASFBot affects (i) human comments mentioning pull requests (PRs) and fixes in issue comments and (ii) the general human comment rate on issues. We apply a regression discontinuity design (RDD) on nine projects that are members of the ASF and which have been active both before
and after the adoption of the ASFBot. Our results indicate (i) a decrease in comments mentioning pull requests and fixes after the bot adoption and (ii) no effect in the number of human comments after the bot adoption. By taking a first step towards understanding how the adoption of ASFBot impacts the issue tracker of projects we can better understand the advantages that the infrastructure of a foundation like ASF provides, and how it affects the commenting behavior of developers in the issue-tracker.
Original language | English |
---|---|
Title of host publication | Proceedings - 2022 Mining Software Repositories Conference, MSR 2022 |
Pages | 112-116 |
Number of pages | 5 |
ISBN (Electronic) | 9781450393034 |
DOIs | |
Publication status | Published - 21 Jun 2022 |
Keywords
- bots
- pull requests
- software engineering
- software process
- GitHub
- Apache Software Foundation
- Bots
- Apache
- ASFBot
- issue-trackers