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Branch Lifecycle

Question: How do projects manage the lifecycle of their version control branches?

Overview

The Branch Lifecycle metric tracks the creation, deletion, and persistence of branches within a version control system. This helps in understanding how a project manages code contributions, feature development, and repository organization. A branch's lifecycle begins with its creation, followed by its possible merging, persistence, or deletion. Some branches are short-lived, focusing on specific features, while others persist for the life of the repository. This metric can reveal patterns in how development teams organize their work and manage repository hygiene. By tracking branch lifecycles, maintainers and contributors gain insights into the health and efficiency of the repository.

Understanding branch lifecycle patterns can also help potential contributors gauge how to engage with a project, offering insights into the repository’s management style and branching practices.

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Data Collection Strategies

Specific description: Git

  • Branching Data from Version Control Systems:
    In the specific case of Git, a significant amount of additional complexity is introduced due to Git’s design as a distributed version control system, which means that Git allows multiple remotes for a single repository (for example, a user’s fork at github.com/user/project and the upstream version at github.com/chaoss/project). More often than not, many individual contributors may work in the same branch locally, and push changes to the remote repository. The local copies, therefore, will sometimes be different than the remote, hosted internally or on platforms like GitHub, GitLab, and BitBucket, since they’re likely either being managed by different people (likely with different branching styles) or they are both being used by one person to “silo” the work they are doing. Data about Git branches can be derived from a Git log directly, or through a Git platform’s API.

  • Local and Remote Data:
    This branch data on the hosted platform may also differ from each developer’s machine, and additionally, different developers may have different branch data on their machine even for the same repository, so it's important to account for both.

  • Document Analysis:
    Guidelines in files such as CONTRIBUTING.md might offer insights into the intended branch management practices.

Filters

  • Collections of Repositories: Analyze branch lifecycles across multiple repositories within a project.
  • Branch Naming Conventions: Compare default branch names (e.g., main) with descriptive branch names, especially in terms of branch persistence.

Visualizations

  • None Specified


References

Contributors

  • None Specified

Additional Information

The usage and dissemination of health metrics may lead to privacy violations. Organizations may be exposed to risks. These risks may flow from compliance with the GDPR in the EU, with state law in the US, or with other laws. There may also be contractual risks flowing from terms of service for data providers such as GitHub and GitLab. The usage of metrics must be examined for risk and potential data ethics problems. Please see CHAOSS Data Ethics document for additional guidance.

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