@@ -10,40 +10,45 @@ info: To determine the technical writer assigned to the Stage/Group associated w
> [Introduced](https://gitlab.com/gitlab-org/gitlab/-/issues/38062) in [GitLab Starter](https://about.gitlab.com/pricing/) 12.7.
Code Review Analytics makes it easy to view the longest-running reviews among open merge requests,
enabling you to take action on individual merge requests and reduce overall cycle time.
Code Review Analytics makes it easy to view the longest-running reviews among open merge requests and
enables you to:
1. Take action on individual merge requests.
1. Reduce overall cycle time.
NOTE: **Note:**
Initially, no data will appear. Data is populated as users comment on open merge requests.
Initially, no data appears. Data is populated as users comment on open merge requests.
## Overview
Code Review Analytics displays a table of open merge requests that have at least one non-author comment. The review time is measured from the time the first non-author comment was submitted.
The code review period for a merge request is automatically identified as the time since the first non-author comment.
To access Code Review Analytics, from your project's menu, go to **{chart}****Project Analytics > Code Review**.
To access Code Review Analytics, from your project's menu, go to **Project Analytics > Code Review**.
You can filter the list of merge requests by milestone and label.
![Code Review Analytics](img/code_review_analytics_v12_8.png"List of code reviews; oldest review first.")
- 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.
The table is sorted by:
-**Review time**: Helping you to quickly find the longest-running reviews which may need intervention
or to be broken down into smaller parts.
- Other columns: Display the author, approvers, comment count, and line change (-/+) 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.
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.
and others who want to understand broad code review dynamics, and identify patterns to explain them.
Code Review Analytics can be used when:
You can use Code Review Analytics to:
- Expose your team's unique challenges with code review.
- Identify improvements that might substantially accelerate your development cycle.
- Your team agrees that code review is moving too slow.
- The [Value Stream Analytics feature](value_stream_analytics.md) shows that reviews are your team's most time-consuming step.
- Analyze the patterns and trends of different types of work that are moving slow.
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:
For example:
- Lots of comments or commits? Maybe the code is too complex.
- A particular author is involved? Maybe more training is required.
