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Category Direction - Code Analytics

Category Code Analytics
Stage Manage
Group Analytics
Maturity Minimal
Content Last Reviewed 2020-02-12

Introduction and how you can help

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:

  1. Comment and ask questions regarding this category vision by commenting in the public epic for this category.
  2. Find issues in this category accepting merge requests.

Overview

Analytics Overview

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.

Where we are Headed

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.

What's Next & Why

We're currently focused on helping engineering managers and project maintainers understand development activity at the project-level. We're focused on shipping small, iterative features that present some insights of value - before moving up into aggregating this information at the group level. Since we've shipped the first iteration of Code Review Analytics, we plan on iterating on customer feedback before pursuing group-level code review analytics.

Target Audience and Experience

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.

Maturity Plan

This category is currently Minimal. The next step in our maturity plan is achieving a Viable state of maturity.

For Code Analytics to be Viable, we should create a clear connection between the Code stage of Value Stream Management and Code Analytics. This category should break down cycle time from the start of development to the end of development, and clearly show an engineering manager where bottlenecks are across the entire cycle time delivery process. At the moment, we only address part of the journey with Code Review Analytics.