@@ -6,23 +6,24 @@ description: "Learn how long your open merge requests have spent in code review,
> [Introduced](https://gitlab.com/gitlab-org/gitlab/issues/38062) in [GitLab Starter](https://about.gitlab.com/pricing/) 12.7.
Code Review Analytics can be used to answer questions like:
- How long do open merge requests spend in code review?
- What distinguishes your longest-running code reviews?
Code Review Analytics makes it easy to view the longest-running reviews among open merge requests,
enabling you to take action on individual MRs and reduce overall cycle time.
NOTE: **Note:**
Initially no data will appear. Data is populated as users comment on open merge requests.
Initially, no data will appear. Data is populated as users comment on open merge requests.
## Overview
Code Review Analytics displays a table of open merge requests, which are considered to be in code review.
Code review starts when a merge request receives its first comment from someone other than the author.
Code Review Analytics displays a table of open merge requests which are currently considered to be in code review.
The code review period for an MR is automatically identified as the time since the first non-author comment.
To access Code Review Analytics, from your project's menu, go to **Project Analytics > Code Review**.
The Code Review Analytics table:
- The table is sorted by review duration, helping you quickly find the longest-running reviews which may need intervention or to be broken down into smaller parts.
- You can filter the list of MRs by milestone and label.
- Columns to display the author, approvers, comment count, and line change (-/+) counts.
- Is sorted by review time, so the longest reviews appear at the top.
- Has columns to display the author, approvers, comment count, and line -/+ counts.
## Use cases
This feature is designed for [development team leaders](https://about.gitlab.com/handbook/marketing/product-marketing/roles-personas/#delaney-development-team-lead)
and others who want to understand broad code review dynamics, and identify patterns to help explain them.
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@@ -30,14 +31,12 @@ and others who want to understand broad code review dynamics, and identify patte
You can use Code Review Analytics to expose your team's unique challenges with code review, and
identify improvements that might substantially accelerate your development cycle.
## Use cases
Code Review Analytics can be used when:
- Your team agrees that code review is moving too slow.
- The [Cycle Analytics feature](cycle_analytics.md) shows that reviews are your team's most time-consuming step.
You can use Code Review Analytics to see what is currently moving slowest, and analyze the patterns
You can use Code Review Analytics to see the types of work that are currently moving the slowest, and analyze the patterns
and trends between them. For example:
- Lots of comments or commits? Maybe the code is too complex.
