Dataset: Issues & Pull Requests
Entity: Pull Requests
Field ID: required_approval_count
Type: Integer
Description: The number of approvals this pull request requires before it can be considered approved. For issues, the value is calculated from resolving pull requests.
Source: App (Pull requests) / Calculated (Issues)
Transformation logic:
Pull Requests: Use the approval settings from the source application. It is defaulted to 1 if null (no approval settings configured).
Issues: Sum the required approvals of all resolving pull requests. Resolving pull requests reference issues via auto-closing keywords.
App Mapping
Github (PRs, Issues) |
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Gitlab (PRs, Issues) |
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Bitbucket (PRs) | Cloud The Minimum number of approvals merge check of the pull request, read from its merge restrictions (
Data Center
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Azure DevOps (PRs, Issues) |
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Jira (Issues) | Calculated: sum of the resolving pull requests |
ClickUp (Issues) | Calculated: sum of the resolving pull requests |
Trello (Issues) | Calculated: sum of the resolving pull requests |
Reporting Use Cases
The Required Approvals field is a critical component for auditing your code review process and ensuring compliance with your quality standards. It provides the baseline for measuring whether a pull request has received sufficient approvals before being merged.
Auditing and Compliance: The most important use of this field is to compare it against the actual approvals a pull request received.
Find Non-Compliant Merges: You can create a high-priority audit report of all merged pull requests that did not meet the minimum approval rule. To do this, create a filter where
state = "MERGED"and then use a custom formula dimension withapproval_count < required_approval_count.PR Review Ratio: This field is the foundation for calculating your team's overall "PR Review Ratio." A custom formula like
ROUND(AVG(IF(required_approval_count == 0, 1, (required_approval_count - required_approval_remaining_count) / required_approval_count)), 2) * 100gives you the percentage of required approvals that were met across all merged pull requests.
Analyzing Review Policies: Using this field as a dimension allows you to understand how your review requirements are configured across different projects.
A bar chart with project_name as the dimension and
AVG(required_approval_count)as the metric can show you the average number of approvals required for each of your repositories, helping you spot inconsistencies in your policies.
Filtering by Review Threshold: You can create reports that focus only on pull requests that have a formal review process.
To exclude pull requests that can be merged without any reviews, you can use a filter like
Required Approvals > 0. This helps you focus your analysis on work that is subject to your team's formal review process.