How can git diff –dirstat be used to measure code churn?

Code churn refers to the quantity of code changes in a project over time. It’s an important metric to track as it can offer insights into the stability of the project, developer activity, and potential risk areas. git diff --dirstat is a useful command that can be used to measure code churn.

The git diff command, in general, allows you to see differences between commits, branches, and more. The --dirstat option provides statistics per directory, allowing you to see changes in a different perspective, which can be especially useful in larger projects.

To understand how to use git diff --dirstat for measuring code churn, let’s first understand the output of this command.

The git diff --dirstat command gives output in the following format:

44.4% src/main/
55.6% src/test/

This tells us that 44.4% of all changes were in the src/main/ directory and 55.6% of all changes were in the src/test/ directory.

To measure code churn using git diff --dirstat, you need to consider two points in the project’s history and calculate the difference. The command will provide a percentage of changes for each directory between the two points.

Here’s an example of how you might use git diff --dirstat:

git diff --dirstat=lines,0 HEAD~30..

In this command, HEAD~30.. refers to the last 30 commits. This command will output the percentage of lines changed in each directory over the last 30 commits. The output format is similar to what was mentioned before, and it’s interpreted in the same way.

If you want to measure code churn in terms of files, you can use:

git diff --dirstat=files,0 HEAD~30..

This will output the percentage of files changed in each directory over the last 30 commits.

Using these commands, you can calculate code churn over different time periods and observe how the project’s development activities change over time.

It’s important to remember that code churn isn’t an absolute metric of project health. High code churn might suggest that a project is undergoing significant changes or refactoring, but it doesn’t necessarily mean the project is in bad shape. Likewise, low code churn could suggest a mature and stable project, but it might also mean the project is stagnating. As such, code churn should be considered alongside other metrics when assessing a project’s status.