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What is code churn and why should you care about it
Code churn refers to the frequency of code updates or edits. It is an indicator of project activity and a key metric in software development. More specifically, code churn measures the number of changes made to the lines of programming code over a given period such as per month or per day. It is expressed as a percentage of the total lines of code in the project.
Code churn is important to consider not only because it’s a measure of the activity of development teams, but also because it gives you an idea of how much work the developers are doing. When code churn is high, there is often something going on behind the scenes that merits closer inspection. Code churn can be caused by many factors, ranging from developers pushing back and forth about design decisions or code implementations to an increase in underlying support activity regarding code and tools.
How to measure code churn and identify its causes
Code churn is a metric derived from source code analysis. It can be calculated using either the edited files or the updated lines of code. If the code is well-tested, it is highly likely that the code change rates are low. So, code churn is a good predictor of software health.
In this article, we will discuss the techniques used in measuring and quantifying code churn using well known tools and techniques. The results would be useful for software engineers to better understand what it means to have active contributions to the code base.
Code Churning
Code churn is actually more than just changes in the source files themselves – it also includes changes in the code that makes up software output (like tests or other runtime behavior). Code churn is a widely-used metric that, when measured with different tools, all go by slightly different names (e.g., technical debt, code smells, technical debt index). Churn may be a good measure of how well documented the code is and other software quality issues.
How to reduce code churn and improve the quality of your codebase
Unmaintained codeThe number of maintenance activities that a software engineer must perform grows with the number of lines of code. If the code is poorly designed and lacks tests, features might not be implemented in the project. The churn could be due to lack of tests and bad code that needs to be rewritten.
Over time, bugs and errors in the codebase will accumulate. A lack of testing means that new features cannot be added as easily because there is no documentation for them.
The longer an application is maintained, the more it becomes difficult to change it. If you change something fundamental, you might have to make changes in a multitude of other places of the application that are affected by the change. Therefore, to maintain the application it is necessary to change the code.
Tools and techniques for measuring and reducing code churn
One of the easiest ways to identify the causes of code change is by using code quality metrics. The Code Quality Metrics survey tool displays both story acceptance and defect density metrics. This can help you identify global code change trends. In case your search for the cause of churn takes you to the product owner, it is worth mentioning that communication with your PO about what he/she wants for product features, and how testing and QA will be conducted can help boost confidence in your coding efforts.
Want to measure what code churn looks like on a specific project? The Code Quality Metrics tool allows users to create custom reports by selecting specific metrics they are interested in measuring.
The Code Quality Metrics tool can display the following summary charts:
– Completeness & stability of code check-ins: The metric shows how much new code was accepted versus rejected. A high value indicates changes were rejected due to their negative impact on stability and/or functionality.
– Engineered for testability, maintainability, and extensibility: The metric calculated from a set of coding guidelines by Codefresh examines the ratio of code that is tested, maintainable and extensible in your project. The higher this ratio, the higher the quality of your code.
– Managed technical debt: This chart shows how much technical debt was created by a release cycle and how much was reduced. A high proportion of “increased” indicates that the release introduced new technical debt.
