Dataset: Issues & Pull Requests
Entity: Pull Requests
Field ID: resolved_issue_metatags
Type: List of text values
Description: The combination of metatags from all resolved issues (via auto-closing keywords), deduplicated and sorted. It is only applicable to pull requests.
Issue metatags combine the labels and sub-types (e.g., Jira issue type) of issues. This field is useful to simplify filtering, especially when creating dashboard-wide filters.
Source: Calculated
Transformation logic:
Pull Requests: Aggregate all results from the
metatagsfield of resolved issues. Metatags are sorted and deduplicated for consistency reasons. Resolved issues are issues that are referenced by a resolving pull request.Issues: Not applicable. This field will always be an empty array
[].
From: |
|
Github (PRs, Issues) | Calculated |
Gitlab (PRs, Issues) | Calculated |
Bitbucket (PRs) | Calculated |
Azure DevOps (PRs, Issues) | Calculated |
JIRA (Issues) | N/A |
ClickUp (Issues) | N/A |
Trello (Issues) | N/A |
Reporting Use Cases
The Resolved Issue Metatags field is an incredibly powerful attribute for accurately categorizing pull requests based on the underlying work they accomplish. By combining the labels and issue types from all resolved issues, it provides a comprehensive and reliable way to understand the "why" behind every pull request.
Accurate Filtering by Work Type: This is the most reliable method for finding pull requests related to a specific business purpose, especially when your primary labeling occurs on issues in a tool like Jira.
Find All Bug Fixes: You can create a definitive report of all pull requests that resolve a bug by using a single filter:
Resolved Issue Metatags contains "bug". This works even if the pull request itself isn't labeled.Track Feature Implementation: Monitor the progress of new features by filtering for pull requests that resolve "Story" or "Feature" issue types with a filter like
Resolved Issue Metatags contains "Story".
Analyzing Development Effort by Category: By using the
FLATTENfunction, you can analyze which types of issues generate the most coding work.To see a breakdown of your team's effort, create a bar chart with the custom formula dimension
FLATTEN(resolved_issue_metatags)and aCOUNT()metric. This will show how many pull requests were created for "bugs," "stories," "tasks," etc.
Creating High-Level KPIs: This field is ideal for use in custom formulas to roll up metrics into meaningful business categories.
Planned vs. Unplanned Work: You can create a pie chart showing the proportion of your team's effort spent on bug fixes versus new features. Use a dimension with a formula like
IF(CONTAINS(resolved_issue_metatags, "bug"), "Bug Fixes", "Feature Work")to categorize each pull request based on the work it resolves.