nw-hotspot

To find the most frequently changed files in a git repository, analyze git change frequency using git log --name-only to count commits per file. This process excludes deleted files and outputs a ranked list of code hotspots to guide maintenance focus and reviews.

Git churn analysis is a technique to identify code hotspots by measuring file change frequency. You should use it to guide maintenance focus, prioritize code reviews, or surface files with high change activity that may indicate technical debt or instability.

Yes, you can use git change frequency ranking as a post-filter to prioritize existing findings. By ranking findings based on file change frequency, you can focus your review efforts on the most actively modified files across your codebases.

You can export git hotspot analysis results for downstream automation using the JSON export mode. This mode outputs the ranked change frequency data as JSON, allowing seamless integration with other tooling and automated maintenance workflows.

Git churn hotspot analysis requires no external dependencies or tools. It operates independently by parsing git log output to count commits per file, excluding deleted files, and generating a ranked result without needing additional software components.

To scope downstream codebase analyses using a pre-filter, run a git hotspot analysis to identify high-change-frequency files first. You then use this ranked output to limit subsequent analysis targets, focusing only on the most volatile areas of the codebase.