[Metrics] Common Metrics - Review Cycle Duration within a Change Request
Description:
- The duration of a review cycle within a single change request.
- This metric provides maintainers with insight on: Code review process decay, as there are more iterations and review cycle durations increase. Process bottlenecks resulting in long code review iterations.
Filters
- Average or Median Duration
optionally filtered or grouped by:
- Number of people involved in review
- Number of comments in review
- Edits made to a change request
- Project or program Organization making the change request
- Time the change request was submitted
- Developers who contributed to a change request
- Change request
- Number of review cycle on a change request
Instances of Implementation Review Cycle Duration is measured as the time length of one review cycle within a single change request. The duration can be calculated between:
- The moment when each review cycle begins, defined as the point in time when a change request is submitted or updated.
- The moment when each review cycle ends, either because the change request was updated and needs a new review or because it was accepted or rejected.
Resource
- CHAOSS: Common Metrics -> When
- link: https://chaoss.community/metric-review-cycle-duration-within-a-change-request/
This issue has not been replied for 24 hours, please pay attention to this issue: @sunshinemingo @wengzhenjie
I think it is hard to identify a change request review cycle with GitHub event data, and even I think review cycle is not a quite objective description, like how can we judge several conversations combination is a review cycle or not?
There is indeed no clear definition regarding what a "review cycle" is. From my understanding it refers to the duration from a new change being requested to the requested change being resolved, which is indeed hard to be implemented based on the data we have now.
Yes, the review resolve is not an event in the GitHub events data, so maybe we can not implement this one shortly, so I will close the issue for now, and maybe we can raise another issue if we have enough data for this.