skip to main content

Explore Research Products in the NSF-PAR

Title: How Do Software Developers Use GitHub Actions to Automate Their Workflows?
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.  more » « less
Award ID(s):
1815503
NSF-PAR ID:
10287964
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Mining Software Repositories Conference (MSR 2021)
Page Range / eLocation ID:
420 to 431
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ( , Empirical Software Engineering)
    Abstract

    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.

     
    more » « less
  2. ; ; ; ; ( , Empirical Software Engineering)
    Abstract

    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.

     
    more » « less
  3. ; ; ; ( , Proceedings of the ACM on Human-Computer Interaction)
    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. 
    more » « less
  4. ; ( , ESEC/FSE 2020: Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering)
    null (Ed.)
    Recommendations between colleagues are effective for encouraging developers to adopt better practices. Research shows these peer interactions are useful for improving developer behaviors, or the adoption of activities to help software engineers complete programming tasks. However, in-person recommendations between developers in the workplace are declining. One form of online recommendations between developers are pull requests, which allow users to propose code changes and provide feedback on contributions. GitHub, a popular code hosting platform, recently introduced the suggested changes feature, which allows users to recommend improvements for pull requests. To better understand this feature and its impact on recommendations between developers, we report an empirical study of this system, measuring usage, effectiveness, and perception. Our results show that suggested changes support code review activities and significantly impact the timing and communication between developers on pull requests. This work provides insight into the suggested changes feature and implications for improving future systems for automated developer recommendations, such as providing situated, concise, and actionable feedback. 
    more » « less
  5. ; ; ; ( , International Conference on Software Engineering, Software Engineering in Society Track)
    Developers in open source projects must make decisions on contributions from other community members, such as whether or not to accept a pull request. However, secondary factors—beyond the code itself—can influence those decisions. For example, signals from GitHub profiles, such as a number of followers, activity, names, or gender can also be considered when developers make decisions. In this paper, we examine how developers use these signals (or not) when making decisions about code contributions. To evaluate this question, we evaluate how signals related to perceived gender identity and code quality influenced decisions on accepting pull requests. Unlike previous work, we analyze this decision process with data collected from an eye-tracker. We analyzed differences in what signals developers said are important for themselves versus what signals they actually used to make decisions about others. We found that after the code snippet (x=57%), the second place programmers spent their time fixating on supplemental technical signals(x=32%), such as previous contributions and popular repositories. Diverging from what participants reported themselves, we also found that programmers fixated on social signals more than recalled. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email