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| Category | Code Analytics |
|---|---|
| Stage | Foundations |
| Group | Optimize |
| Maturity | Minimal |
| Content Last Reviewed | 2020-08-06 |
Thanks for visiting the direction page for Code Analytics in GitLab. This page is being actively maintained by the Product Manager for the Analytics group. If you'd like to contribute or provide feedback on our category direction, you can:
Value Stream Management makes up the framework of our analytics strategy, and Code Analytics is a deep-dive into the Create stage. This category seeks to help our users understand how to help developers write more efficient code, unblock merge requests, and find bottlenecks that emerge during the process of writing code.
We see Code Analytics as a deep-dive into the code-writing stage of your value stream (or cycle time). It begins when a developer begins working on a new improvement, continues through code review, and typically ends when a merge request is successfully merged into a branch. We attempt to measure this activity in the Code stage of Value Stream Analytics, but should evolve this definition further to ensure we're including full cycle time.
Code Analytics will break cycle time down by project, group, and aggregate coding activity across an instance. Since code review is an integral part of cycle time - and where delays can happen frequently - We've started with Code Review as a focus. We intend to iterate on this feature and add more complexity and insight over time.
We're currently focused on helping engineering managers and project maintainers understand development activity at the project-level. Since we've shipped the first iteration of Code Review Analytics, we have paused awaiting further customer feedback.
We've shifted over to prioritize throughput as a first-class feature to help engineering teams understand merge request activity. We'll iterate and improve this feature with the help of our internal customers at GitLab.
Afterward, we anticipate moving back to Code Review Analytics and prioritizing ideas like a MR reviewer dashboard.
We believe the target audience for Code Analytics is a development team lead, who seeks to understand their codebase and to take data driven prioritization and management decisions.
This category is currently Minimal. The next step in our maturity plan is achieving a Viable state of maturity.