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Software projects frequently use automation tools to perform repetitive activities in the distributed software development process. Recently, GitHub introducedGitHub Actions, a feature providing automated workflows for software projects. Understanding and anticipating the effects of adopting such technology is important for planning and management. Our research investigates how projects useGitHub Actions, what the developers discuss about them, and how project activity indicators change after their adoption. Our results indicate that 1,489 out of 5,000 most popular repositories (almost 30% of our sample) adoptGitHub Actionsand that developers frequently ask for help implementing them. Our findings also suggest that the adoption ofGitHub Actionsleads to more rejections of pull requests (PRs), more communication in accepted PRs and less communication in rejected PRs, fewer commits in accepted PRs and more commits in rejected PRs, and more time to accept a PR. We found similar results when segmenting our results by categories ofGitHub Actions. We suggest practitioners consider these effects when adoptingGitHub Actionson their projects.

 

Software bots have been facilitating several development activities in Open Source Software (OSS) projects, including code review. However, these bots may bring unexpected impacts to group dynamics, as frequently occurs with new technology adoption. Understanding and anticipating such effects is important for planning and management. To analyze these effects, we investigate how several activity indicators change after the adoption of a code review bot. We employed a regression discontinuity design on 1,194 software projects from GitHub. We also interviewed 12 practitioners, including open-source maintainers and contributors. Our results indicate that the adoption of code review bots increases the number of monthly merged pull requests, decreases monthly non-merged pull requests, and decreases communication among developers. From the developers’ perspective, these effects are explained by the transparency and confidence the bot comments introduce, in addition to the changes in the discussion focused on pull requests. Practitioners and maintainers may leverage our results to understand, or even predict, bot effects on their projects.

 

Software bots automate tasks within Open Source Software (OSS) projects' pull requests and save reviewing time and effort ("the good"). However, their interactions can be disruptive and noisy and lead to information overload ("the bad"). To identify strategies to overcome such problems, we applied Design Fiction as a participatory method with 32 practitioners. We elicited 22 design strategies for a bot mediator or the pull request user interface ("the promising"). Participants envisioned a separate place in the pull request interface for bot interactions and a bot mediator that can summarize and customize other bots' actions to mitigate noise. We also collected participants' perceptions about a prototype implementing the envisioned strategies. Our design strategies can guide the development of future bots and social coding platforms. 

Software bots are used to streamline tasks in Open Source Software (OSS) projects' pull requests, saving development cost, time, and effort. However, their presence can be disruptive to the community. We identified several challenges caused by bots in pull request interactions by interviewing 21 practitioners, including project maintainers, contributors, and bot developers. In particular, our findings indicate noise as a recurrent and central problem. Noise affects both human communication and development workflow by overwhelming and distracting developers. Our main contribution is a theory of how human developers perceive annoying bot behaviors as noise on social coding platforms. This contribution may help practitioners understand the effects of adopting a bot, and researchers and tool designers may leverage our results to better support human-bot interaction on social coding platforms. 

Automated tools are frequently used in social coding repositories to perform repetitive activities that are part of the distributed software development process. Recently, GitHub introduced GitHub Actions, a feature providing automated workflows for repository maintainers. Although several Actions have been built and used by practitioners, relatively little has been done to evaluate them. Understanding and anticipating the effects of adopting such kind of technology is important for planning and management. Our research is the first to investigate how developers use Actions and how several activity indicators change after their adoption. Our results indicate that, although only a small subset of repositories adopted GitHub Actions to date, there is a positive perception of the technology. Our findings also indicate that the adoption of GitHub Actions increases the number of monthly rejected pull requests and decreases the monthly number of commits on merged pull requests. These results are especially relevant for practitioners to understand and prevent undesirable effects on their projects. 

Software bots are used by Open Source Software (OSS) projects to streamline the code review process. Interfacing between developers and automated services, code review bots report continuous integration failures, code quality checks, and code coverage. However, the impact of such bots on maintenance tasks is still neglected. In this paper, we study how project maintainers experience code review bots. We surveyed 127 maintainers and asked about their expectations and perception of changes incurred by code review bots. Our findings reveal that the most frequent expectations include enhancing the feedback bots provide to developers, reducing the maintenance burden for developers, and enforcing code coverage. While maintainers report that bots satisfied their expectations, they also perceived unexpected effects, such as communication noise and newcomers' dropout. Based on these results, we provide a series of implications for bot developers, as well as insights for future research.