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Time to First Review

Time to First Review

Owned by Chris Boys
Last updated: Mar 17, 2021
2 min read

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

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

Code reviews in reasonable quantity, at a slower pace for a limited amount of time results in the most effective code review

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.

Resources

  1. Dias, H., The anatomy of a perfect pull request, 2018, <The anatomy of a perfect pull request >

  2. Osepchuk, B., Optimal pull request size, 2017, <https://smallbusinessprogramming.com/optimal-pull-request-size/>

  3. Riosa, B. The (written) unwritten guide to pull requests, 2016, <The (written) unwritten guide to pull requests - Work Life by Atlassian > 

  4. Dias, H., The anatomy of a perfect pull request, 2018, <https://opensource.com/article/18/6/anatomy-perfect-pull-request> 

  5. Hewa, G., How Big is Your Pull Request?, 2017, <https://hackernoon.com/how-big-is-your-pr-32c4d67ad76c> 

  6. 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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