Code Ownership at Scale: Who Knows What in Your Codebase

The problem lies in outdated code ownership documentation like CODEOWNERS files, which become inaccurate quickly. Code ownership is dynamic, changing as people's roles and contributions evolve. Static documentation fails to reflect this evolving reality, leading to knowledge gaps. Git, however, contains the data needed to determine actual code ownership through authorship, review patterns, and change velocity. Key metrics for determining code ownership include bus factor, knowledge distribution, review coverage, and ownership decay. Bus factor helps assess knowledge concentration, while knowledge distribution indicates healthy team contributions. Review coverage identifies potential risks in code quality. Ownership decay highlights inactive contributors who may not be knowledgeable. Utilizing these metrics allows a better understanding of code ownership compared to static files. Actionable insights from ownership data drive positive behaviours when it comes to assigning tickets or planning complex features. Real-time insights from contribution patterns is key to resolving the problems of outdated ownership documentation. Tools like Glue offer insights into code ownership derived from active contribution patterns, as opposed to outdated information.