What is Time to First Review
Time to merge measures how fast a Pull Request (PR) was merged after creating it.
Why Time to First Review matters
Time to first Review affects your author’s ability to minimise context switching and supports the team to make frequent deployments into production.
PRs that are taking a long period of review time (several hours or more) relative to their size may indicate that your team’s review process is blocking.
What ‘good’ Time to First Review looks like
A short time to merge indicates a culture of strong team responsiveness, collaboration and continuous delivery. PRs are opened and merged within a day reflect more mature practices. This is made possible by the author’s well constructed title (self-explanatory), description (
How Umano measures Time to First Review
For each of the PRs that are merged during a particular interval, Umano takes the time difference between when the PR was created and the time when it was merged.
Practices that influence this measure
Number of comments on a PR
Number of tasks on a PR
Size of the PR
Number of issues addressed in a PR
Number of times a PR has been reviewed
Time to first review
What’s included?
Each model looks and specific activities within the tools. Below a list of activities that contribute to Time to First Review and activities that do not have an impact on this metric.
Included | Not included |
|---|---|
All Pull Requests in selected repositories. | If the review is done by the author him/her-self then it is not considered a review. Any additional review undertaken after the first review. |
Tips for improving Time to First Review
| Tip |
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Code reviews in reasonable quantity, at a slower pace for a limited amount of time results in the most effective code review |
| Tip |
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Submit Pull Requests on the day the code is ready for review, rather than waiting to submit all requests at the back of the sprint and causing a backlog for your peers to work through |
| Tip |
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Add titles and descriptions: the more context that authors provide, the faster a reviewer can understand the logic of what has been submitted for review. |
| Tip |
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Titles should be self-explanatory |
| Tip |
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Make the description useful by describing WHAT has changed, WHY this PR exists, HOW it is meant to work, and use screenshots where appropriate |
Resources
Dias, H., The anatomy of a perfect pull request, 2018, <https://medium.com/@hugooodias/the-anatomy-of-a-perfect-pull-request-567382bb6067 >
Osepchuk, B., Optimal pull request size, 2017, <https://smallbusinessprogramming.com/optimal-pull-request-size/>
Riosa, B. The (written) unwritten guide to pull requests, 2016, <https://www.atlassian.com/blog/git/written-unwritten-guide-pull-requests >
Dias, H., The anatomy of a perfect pull request, 2018, <https://opensource.com/article/18/6/anatomy-perfect-pull-request>
Hewa, G., How Big is Your Pull Request?, 2017, <https://hackernoon.com/how-big-is-your-pr-32c4d67ad76c>
Yu, Y., Wang, H., Filkov, V., Devanbu, P. and Vasilescu, B., 2015, May. Wait for it: Determinants of pull request evaluation latency on GitHub. In Mining software repositories (MSR), 2015 IEEE/ACM 12th working conference on (pp. 367-371). IEEE.