Code rot is a common problem among engineering teams. It can compound unless it is well-managed.
Just like how we need to nurture our plants to grow or else they will be withered. The same should be done with code, otherwise, it will rot.
So, let’s delve deeper into the concept of Code rot, ways to recognize it, and how to address it.
Code rot: Definition
Also known as software rot or software decay, It refers to the deterioration in the performance of a piece of code. It doesn’t mean code doesn’t break down or rot away. Rather, the quality of the code starts degrading over time, emphasizing the importance of clean code practices.
This further makes the software faulty, unusable, or need upgradation. If not taken care of in the long run, it can also directly impact the team’s productivity and morale.
2 types of code rot
Active Code Rot:
Active rot shows signs of code while they are actively handled and maintained. Also known as Gradual Decay, these codes slowly worsen in small details. The common type of code rot can be found in every code base to a varying degree. This is because most software requires constant updates and bug fixing. Hence, deviating the program from its original design.
Dormant Code Rot:
Dormant rot is easy to detect. This code isn’t being touched constantly which makes them useless as the rest of the application upgrades. The reasons could vary. A few of them include API no longer working, Hardware and platforms have stopped working, and missing device adaptations.
Recognizing code rot
Code is fragile:
In this case, the code breaks in many places whenever a change is made. The code isn’t stable as software becomes difficult to maintain. When the code is fragile, every new change introduces several new defects. Even when the areas aren’t related to each other. They can be either detected early by an automated testing suite or found in production by end-users.
Software metrics are declining:
Declining software metrics don’t always indicate code rot, but they can be a warning sign that the code needs to be reviewed. Sometimes, it’s a slow deterioration, showing that the code isn’t as healthy as it once was, and action should be taken to resolve it. A few of the metrics that can collect software codebase health data include Coupling, Cyclomatic Complexity, and Test Coverage. These metrics provide valuable insights into software complexity and can guide improvements.
Code is rigid:
When the code is hard to change, it can be a warning sign of code rot. Even when it is a simple change, it takes longer than expected. Moreover, one change may lead to other changes as well. The code becomes less adaptable to changes and prone to errors, instability, and crashes. As a result, this leads to a slowing down of the development process.
Increase in time to deliver value:
In continuation of the above point, code rigidity can also increase the time to deliver value. As the code is in an unhealthy state, more time will be needed to add new features. Hence, it takes longer to ship new features to the customers. Moreover, the developers may fear managing non-critical issues as they aren’t sure of the full impact of the change.
Documentation is outdated:
When the documentation isn’t updated or maintained for a long time, it gets out of sync with the code. This makes it misleading. As a result, it creates confusion and errors for developers to rely on it. If the documentation remains outdated for a long time, it can make the end users unhappy with the product.
Addressing code rot
Create standardized coding guidelines:
You can start by defining what Healthy software stands for in your organization. Establish a set of common coding guidelines and practices for your team members. It allows them to be on the same page and move in the same direction. Moreover, it creates a social contract between the team and lets them consistently write code.
Use software metrics:
Software metrics may not necessarily identify code rot. But it can help in knowing the quality and health of the codebase. Various metrics such as cycle time, code churn, and cyclomatic complexity let the developers know how the code is performing. It can identify code smells and technical debt, track their changes over time, and much more. Hence, helping in further inspection.
Software metrics can also help in knowing the blind spots within your software development. Hence, it helps developers to know which areas need refactoring to enhance the overall quality of the code. Refactoring them in small, frequent iterations lets the code adapt better to new environments and improves its quality and longevity. This approach also assists in the gradual improvement of the code base and keeps it manageable, ensuring that your test suite remains effective.
While manual testing may take a lot of time, you can go for automated testing of the code. However, ensure that the code is written with testing in mind. It lets you know whether the code is working as expected. Moreover, if any recent changes are made, automated testing lets the developers know any previously working functionality has been affected. Hence, helping in detecting the issues early.
Mentor new developers:
Lastly, after hiring the right set of developers, ensure that you train them regarding coding guidelines. Make them understand how refactoring should be done often and coding best practices. Try aligning them with other developers. Create a culture of continuous learning and foster open communication in your organization.
While code rot is a universal problem, It can still be prevented. Take care of your code base often. If any issue is detected, take the necessary steps at the earliest.
Typo, an intelligent engineering platform, can help in identifying SDLC metrics. It can further help in detecting blind spots and reducing code rot.
Book a demo with our Typo team today!