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Code

Overview of these metrics:

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Code Review
Overview of these metrics:

  1. Open Pull Requests

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    4. What should I take away from this data?

    Pull Request Approvals

Open pull requests represent new features or bug fixes waiting for review. Identifying aging or old pull requests can help you discover features that have been abandoned or have other issues introduced into production.

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  1. Pull Request Comments

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    Approvals

One indicator of code quality is if new code and features are peer-reviewed. Having other engineers look at code and approve it helps increase confidence in the codebase. Looking at approvals on Pull Requests can help visualize this.

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    3. What should I take away from this data?


  1. Pull Request Comments

One indicator of code quality is if new code and features are peer-reviewed. HHaving other engineers review the code and add comments helps increase confidence in the codebase and ensure the code is easily understood by others. Looking at approvals on Pull Requests can help visualize this.

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  1. Pull Request Cycle TimeTime

Evaluate your engineering teams' productivity by tracking the amount of time work starts development to the time it's deployed to production.

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  1. Pull Request Size

The size of a Pull Request can be an indicator of quality and risk if too large. Use this metric to spot risky code and prevent an increase in bugs created.

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    Pull Requests Merged
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  1. Pull Requests Merged

Understanding who is merging Pull Requests will help you understand the distribution of work.(Guessing on this one)

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Builds

  1. Average Build Delay

The average amount of time a developer has to wait for a build to successfully run as an indicator of developer productivity.

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    Average Build Time

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  1. Average Build Time

The average amount of time that it takes a build to complete. Long build times can cause delays in developer activity and impact productivity.

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  1. Build Success Rate

View Build Success Rate by team member. Managing features by branches leads to a cleaner, well-maintained code. Looking at how the users are following standards will identify risks in your code and areas for developers to improve.

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