Technical debt is a pervasive challenge in software development, especially in fast-paced Scrum environments. Left unchecked, it can slowly drain your team's productivity and lead to a messy, fragile codebase. It annoys developers, managers, executives, and customers alike.
Thus, finding and fixing it is critical to a well-performing team and a well-designed product. This comes down to understanding and measuring the correct metrics for technical debt, then using these metrics within your sprints to fix persistent debt while also building out a framework to remove the process and organizational issues that caused the debt in the first place. Here’s how.
How to Measure Technical Debt
Peter Drucker never said the apocryphal words “what gets measured gets managed,” but that doesn’t make the statement any less accurate. First, you have to measure your technical debt to manage it. You can't fix what you don't know, and in the context of Scrum and Agile development, this means surfacing quality issues and making them visible to the entire team.
We’ve discussed what technical debt means before, so we won’t reiterate the same problems. But, briefly, several code quality metrics can help quantify technical debt:
- Code Complexity: Cyclomatic complexity measures the number of linearly independent paths through a code block. Higher complexity makes it harder to understand, test, and maintain code. For example, a function with nested if/else statements and loops would have high complexity. Aim to keep cyclomatic complexity under 10 per function.
- Code Duplication: Duplicated code is a common programming error that bloats the codebase and leads to maintainability issues, as bugs need to be fixed in multiple places. Tools can identify copy-pasted or structurally similar code. As a rule of thumb, at most 5% of your code should be duplicates.
- Code Smells: Code smells are characteristics that indicate deeper quality problems. Examples include long methods, large classes, too many parameters, and poorly named variables. Set standards like no functions over 20 lines and no files over 200 lines to avoid code smells.
- Test Coverage: Automated tests are essential for catching regressions and enabling safe refactoring. Track the % of code covered by tests and set a target of 80%. More importantly, focus on the quality of tests for critical and complex code.
- Quality Index: Some tools, such as Codacy, provide a composite "quality index" score or grade based on metrics like complexity and lines of code. Establish a target score under which code needs refactoring.
How do you collect these metrics? The simplest option is integrating static code analysis tools into your CI/CD pipeline to analyze each build automatically. Codacy Quality will give you insight into:
- Issues
- Code Duplication
- Code Complexity
- Coverage
- Grade
However, metrics are just indicators. Not all debt is created equal. You need to look deeper to identify the most critical issues. Conduct periodic code audits manually to examine quality hot spots flagged by the tools. Use this analysis to agree on target metric thresholds that make sense for your context. Update these targets over time as you make progress.
Making technical debt concrete through disciplined measurement gives the team a framework for objectively prioritizing and tackling it. Without measurement, technical debt becomes an invisible monster that is easy to ignore until it comes back to bite you.
How to Manage Technical Debt in Scrum
In a Scrum context, managing technical debt is about making it visible, allocating time to address it, preventing new debt, and continuously monitoring and adapting.
Make Technical Debt Visible
The first step is to surface technical debt issues and make them visible to the entire Scrum team, including the Product Owner.
You can do this by including debt in the backlog. Create user stories or tasks in your backlog specifically for refactoring or fixing technical debt. For example: "Refactor the payment processing service to improve maintainability and enable easier addition of new payment methods."
You can also prioritize debt based on "interest rate." Not all debt is equal. Estimate each debt item's "interest rate" based on how much it's slowing the team down or risking bugs. Use this to prioritize debt stories in your backlog.
More pragmatically, you can visualize debt on your board. A separate swim lane on your Scrum board for technical debt stories helps keep debt items visible during sprint planning and daily stand-ups. This is also a way to make quality metrics visible. You can display code quality metrics (complexity, duplication, test coverage, etc.) on dashboards that are visible to the whole team and review trends in these metrics during sprint retrospectives.
Allocate Time to Pay Down Debt
Dedicate time in each sprint to pay down technical debt.
Allocate a fixed percentage (e.g., 20%) of each sprint's refactoring and debt reduction capacity. Treat this time as non-negotiable, just like you would for critical bug fixes. Every few sprints, dedicate an entire sprint to paying down debt. This can be a good opportunity for larger refactorings that wouldn't fit in a regular sprint.
For example, let's say your team has identified a critical piece of legacy code that's become a significant source of bugs and developer frustration. This complex, monolithic component is tightly coupled with multiple parts of the system, so refactoring it will be a significant undertaking.
In this case, you might dedicate an entire "debt sprint" to tackling this component. The team breaks down the refactoring work into manageable tasks: extracting reusable modules, improving test coverage, updating documentation, etc. They agree to put all new feature development on hold for this sprint so that they can focus solely on this refactoring.
By the end of the sprint, the legacy component had been broken down into smaller, more maintainable pieces. The code was cleaner, better tested, and easier for developers to work with. While it required a short-term sacrifice in terms of new feature development, the long-term benefits of increased productivity and reduced bug risk made it well worth the investment.
The key is to make this dedicated debt-reduction time a regular part of your sprint rhythm, not just a one-off event. By consistently allocating time to refactoring, you prevent debt from accumulating to unmanageable levels.
Prevent New Debt
It's not enough to fix existing debt; you must also prevent new debt from being incurred. This might mean changing your Definition of Done. For instance, include quality criteria (e.g., "Code complexity below X," "80%+ test coverage") in your team's Definition of Done so no story is considered complete unless it meets these standards. Two other absolutes are:
- Code reviews: Conduct peer code reviews on all changes to catch quality issues and potential debt early. Use automated tools to guide these reviews.
- Coding standards: Agree on and enforce coding standards and best practices. Use static code analysis tools to check compliance automatically.
Managing technical debt is an ongoing process. In each sprint retrospective, review trends in your quality metrics. Discuss any red flags and brainstorm ways to address them. When debt is identified, dig into the root causes:
- Is it due to a rush to meet deadlines?
- Lack of skills in a particular area?
- Flawed architecture decisions?
Address these underlying issues and then, based on your learnings, continuously update your team's practices around managing debt, such as adapting your Definition of Done, refactoring budget, and coding standards.
For example, imagine that in a sprint retrospective the team notices that code complexity has been steadily increasing. Upon digging in, they realize it's mostly in the user management module. The root cause is that many rushed, piecemeal updates have been made to handle different user roles and permissions.
The team prioritizes a refactoring story for the next sprint: "Redesign user role and permission system to improve maintainability and extensibility." They budget two days for this in the sprint. They also update their Definition of Done to include: "All new code in the user management module must have a complexity score below 5." And they dedicate their next "debt sprint" to a comprehensive module refactoring.
Making technical debt management a regular part of the Scrum process becomes a shared, proactive responsibility rather than an afterthought. The key is to keep debt visible, dedicate time to it, and continuously improve your processes based on learnings.
How to Avoid Technical Debt
While some technical debt is inevitable, especially in fast-moving Scrum environments, there are proactive strategies you can employ to minimize the accumulation of new debt. The key is to build practices that promote code quality and maintainability from the start of the development process.
For example, imagine your team is building a new microservice for processing payments. Rather than trying to design the ultimate, all-encompassing payment system upfront, you start with a simple design that handles the most common payment scenarios. You break the functionality into small, focused services (e.g., payment validation, fraud detection, payment execution). The team writes extensive unit and integration tests for each service, practicing TDD where possible.
As you build the system, you regularly deploy to production using a fully automated CI/CD pipeline that includes static code analysis and performance tests. The team conducts bi-weekly architectural reviews to evaluate the growing system and make adjustments. Developers work in pairs and practice continuous refactoring to keep the code clean.
By taking a proactive, quality-focused approach from the start, the team can incrementally deliver a robust payment system without incurring significant debt.
Avoiding technical debt in Scrum is about building quality from the start through practices like simple design, automated testing, CI/CD, and regular architectural reviews. By making these practices an integral part of your development process, you can minimize new debt and keep your codebase healthy over the long term.
Beware the Impact of Technical Debt
Technical debt is dangerous. It is going to suck up your developer’s time and your company’s money. It will stop you from developing new features for your customers and make those customers irate where the debt manifests as customer-facing issues.
This measuring, managing, and avoiding technical debt is paramount. Doing this in Scrum requires a multi-faceted, proactive approach. By objectively measuring debt with an analysis tool such as Codacy Quality, making it visible in your process, dedicating time to addressing it, and building quality practices from the start, you can keep debt under control and maintain a healthy codebase.
Remember, the goal isn't to eliminate debt entirely but to manage it strategically so it doesn't overwhelm your project. With disciplined practices and a commitment to continuous improvement, your team can deliver value sustainably, sprint after sprint.
