What is Time to first Review
Time to first Review measures how responsive your team is picking up and reviewing a Pull Request (PR), as measured by the first approval or decline made per PR.
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
Inspection rates typically hover at 60 minutes per 500 lines of code (LOC). Whilst it can be tempting to focus on speed at the expense of a quality review, this defeats the purpose of the task at hand.
How Umano measures Time to first Review
Identify the time taken from when the author submits a PR to when the first approval or first decline is made for that PR during each given interval.
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
Reviewers are assigned in the PR
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. |
Tips for improving Time to first Review
Code reviews in reasonable quantity, at a slower pace for a limited amount of time results in the most effective code review
Break down larger features into smaller Pull Requests, ideally between 200-400 LOC for fast and effective defect detection
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
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.
Titles should be self-explanatory
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.
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