September 16th, 2024 | by Radosław Chmielniak
Understanding and Identifying Technical Debt
Table of contents
What Is Technical Debt?
Technical debt is a concept that resonates with every software engineer. Just like financial debt, it involves trade-offs and consequences. At its core, technical debt represents the shortcuts, compromises, and suboptimal decisions made during software development. These choices accumulate over time, impacting the quality, maintainability, and long-term viability of a project. The term was popularized by Ward Cunningham, who drew parallels between software development and financial borrowing. Just as financial debt incurs interest, technical debt accrues “interest” in the form of increased complexity, bugs, and maintenance costs.
- Code Debt – This type of debt arises from hasty coding practices. It includes messy code, duplicated logic, and inadequate comments. Code debt makes future enhancements difficult and increases the likelihood of defects. A lot of such issues are introduced by the “Quick Fixes” where the time is crucial but the method of solving the problem is not fully appropriate. If it will not be refactored just after or it is not well documented then after some time no one will know how it is supposed to work correctly and it will remain in an impropriate state.
- Design Debt – Design decisions that prioritize short-term gains over long-term stability contribute to design debt. Examples include poor architecture, lack of modularity, and insufficient scalability planning. It is important to design the application according to the aimed goal and based on this choose the proper tools, frameworks, and roadmap because these differ on the chosen approach and may be even impossible to change in the later stages of the development. For example, small webpage technology for a furniture store will be different if there is a plan to create a store on it in the later stage, as the shop may already have an internal CMS system to which we would need to integrate.
- Test Deb – Neglecting testing activities leads to test debt. Insufficient test coverage, flaky tests, Inefficient testing environments, and postponed test automation fall into this category. Creating automated tests adds some additional effort at the beginning, but it saves a lot of time after as the regression testing may only require running the well-prepared tests and we can get the results in a few minutes, without human intervention. They are also irreplaceable when the code dept is repaid by doing smaller refactoring or bigger code/architectural change – the outcome should be then the same as before the modification.
Apart from the above, there can be also depth in architecture, build, defects, documentation, infrastructure, people, processes, requirements, services, tests, and automation. As we can see the depth can be made in almost all aspects of software development which makes the technical dept term even more crucial in the whole process of creating a successful and easy-to-maintain product.
- Intentional Debt – In this case, the team is aware of existing issues but may choose not to address them due to various reasons (e.g., avoiding more severe consequences or further exacerbating the debt).
- Unintentional Debt – Here, the team is unaware of existing issues, leading to the maintenance of outdated systems or the implementation of additional solutions that worsen the problem.
How to Identify Technical Debt?
Recognizing technical debt early is crucial. Here are some signs to watch out for:
- Complex Code – If your codebase resembles a tangled web, technical debt may be lurking. High cyclomatic complexity, deeply nested conditionals, and convoluted control flow are red flags.
- Code Duplication – Repeated code fragments indicate design debt. Duplication makes maintenance harder and increases the chances of inconsistencies. Every change in the logic will require to be made in multiple places, which can be postponed when doing the “Quick-Fix” causing there will be 2 similar codes, but we will be unsure which one is the proper one.
- Documentation Gaps – Inadequate documentation is a sign of technical debt. Clear comments, API documentation, and architectural diagrams are essential for understanding the system. In the documentation, we need to be strict to not allow the recipient to presume what is the behavior. Everyone may have his understanding of the functionality – it is called a False-Consensus Effect and may lead to many problems.
- Quick Fixes – Frequent band-aid solutions—quick patches to address immediate issues—accumulate technical debt. These patches often lack elegance and perpetuate underlying problems. It is strictly recommended to have the proper fix in the road map just after the quick one or have at least it well documented to get back to it in a quieter project time.
How to Measure and Assess Technical Debt?
While there’s no universal standard for measuring technical debt, it’s essential to consider its broader impact on team dynamics, project timelines, and overall software quality. By employing both qualitative and quantitative measures, teams can gain a comprehensive understanding of their technical debt. This insight allows for informed decision-making and prioritization of tech debt reduction efforts, ensuring that the software remains robust, scalable, and maintainable over time:
Qualitative Assessments:
- Code Reviews – Regular code reviews are essential for uncovering hidden technical debt. During these peer reviews, developers examine each other’s code to identify issues. The most common issues reported in the reviews are code smells (too long methods, duplicated code, complex logic), anti-patterns, and best practices violations. The best and most commonly used practice is to review the code before merging it to the main code branch – in this case, we will avoid having poor-quality code in the main branch and all the issues reported will need to be fixed before the code merge.
- Static Analysis Tools – These tools automatically scan code for potential issues, and code quality, and detect bugs, security vulnerabilities, and code smells. They can be run locally or using CI/CD pipelines. It is often connected with the code reviews in the code merging activity (like Pull Requests in GIT) where all quality checks need to pass before the merge can happen.
Quantitative Measures:
- Technical Debt Ratio: TDR is a metric used to provide insights into the quality of code in a software project by comparing the cost of fixing the technical debt against the total cost of developing the code. Here’s how you can calculate it:
TDR = (Cost to Fix Technical Debt / Total Development Cost) * 100%
Cost to Fix Technical Debt is the estimated effort required to fix all known issues and code smells in the codebase, often measured in man-days or hours.
Total Development Cost includes the total effort spent on developing the code, which can encompass designing, coding, testing, and deploying the software. - Cyclomatic Complexity: measures code complexity based on control flow. Higher complexity correlates with increased technical debt. It is important to aim for simpler code with fewer decision points to reduce cyclomatic complexity. It improves the code readability as well.
Strategies for Managing and Repaying Technical Debt
Managing technical debt effectively hinges on two main strategies: prevention and repayment. Prevention is about being proactive—identifying potential technical debt early, raising awareness among the team, and implementing procedures that help avoid its accumulation. This could involve setting coding standards, conducting thorough code reviews, and using static analysis tools to catch issues before they become entrenched.
- Set “Repayment Terms” – Just like financial debt, technical debt needs a repayment plan. Identify where debt exists and create a timeline for paying it off. Regularly audit your technical debt and ensure your company doesn’t carry a high debt ratio. Remember, unchecked technical debt can linger indefinitely unless you actively manage it.
- Listen to Your Developers – Developers working on maintenance tasks are often closest to the technical debt. Pay attention to their insights and feedback to understand where the debt exists within the codebase and collaborate with your team to address it effectively.
- Prioritize Debt Reduction – Make technical debt reduction a priority. Allocate time and resources specifically for addressing debt. Set coding standards and guidelines to prevent the accumulation of new debt. Regular code reviews help maintain quality.
Repayment, on the other hand, is about addressing the technical debt that has already accumulated. It requires prioritizing the reduction of debt, incentivizing quality work, and refactoring the codebase to improve its health. This isn’t just about fixing what’s broken; it’s about making strategic improvements to the code that will pay dividends in the future.
Automate Testing and Refactor Code
Write automated tests for the regression test scenarios and ensure code stability. Then use this automated test to ensure that the code is working as expected after the refactoring. Refactor existing code to improve its quality. Break down large, complex functions, eliminate duplicated code, and enhance readability.
Documentation Enhancement
Invest in comprehensive documentation. Clear explanations reduce ambiguity and facilitate maintenance.
Development Practices
Adopt practices like test-driven development (TDD), continuous integration, and pair programming. Train your specialists on how to write a clean code, refactor successfully the code, prepare reusable or automate parts of their work.
Prioritization
Use cost-benefit analysis to prioritize debt repayment. Balance feature development with debt reduction. Here the TDR ratio can help a lot, having in mind that if later we will start the repayment that the ration should be higher. Once the dept will be repaid we can lower down the ratio, but it should never be close to zero or even zero.
Automate Testing and Refactor Code
Write automated tests for the regression test scenarios and ensure code stability. Then use this automated test to ensure that the code is working as expected after the refactoring. Refactor existing code to improve its quality. Break down large, complex functions, eliminate duplicated code, and enhance readability.
Documentation Enhancement
Invest in comprehensive documentation. Clear explanations reduce ambiguity and facilitate maintenance.
Development Practices
Adopt practices like test-driven development (TDD), continuous integration, and pair programming. Train your specialists on how to write a clean code, refactor successfully the code, prepare reusable or automate parts of their work.
Prioritization
Use cost-benefit analysis to prioritize debt repayment. Balance feature development with debt reduction. Here the TDR ratio can help a lot, having in mind that if later we will start the repayment that the ration should be higher. Once the dept will be repaid we can lower down the ratio, but it should never be close to zero or even zero.
Automate Testing and Refactor Code
Write automated tests for the regression test scenarios and ensure code stability. Then use this automated test to ensure that the code is working as expected after the refactoring. Refactor existing code to improve its quality. Break down large, complex functions, eliminate duplicated code, and enhance readability.
Documentation Enhancement
Invest in comprehensive documentation. Clear explanations reduce ambiguity and facilitate maintenance.
Development Practices
Adopt practices like test-driven development (TDD), continuous integration, and pair programming. Train your specialists on how to write a clean code, refactor successfully the code, prepare reusable or automate parts of their work.
Prioritization
Use cost-benefit analysis to prioritize debt repayment. Balance feature development with debt reduction. Here the TDR ratio can help a lot, having in mind that if later we will start the repayment that the ration should be higher. Once the dept will be repaid we can lower down the ratio, but it should never be close to zero or even zero.
Automate Testing and Refactor Code
Write automated tests for the regression test scenarios and ensure code stability. Then use this automated test to ensure that the code is working as expected after the refactoring. Refactor existing code to improve its quality. Break down large, complex functions, eliminate duplicated code, and enhance readability.
Documentation Enhancement
Invest in comprehensive documentation. Clear explanations reduce ambiguity and facilitate maintenance.
Development Practices
Adopt practices like test-driven development (TDD), continuous integration, and pair programming. Train your specialists on how to write a clean code, refactor successfully the code, prepare reusable or automate parts of their work.
Prioritization
Use cost-benefit analysis to prioritize debt repayment. Balance feature development with debt reduction. Here the TDR ratio can help a lot, having in mind that if later we will start the repayment that the ration should be higher. Once the dept will be repaid we can lower down the ratio, but it should never be close to zero or even zero.
Automate Testing and Refactor Code
Write automated tests for the regression test scenarios and ensure code stability. Then use this automated test to ensure that the code is working as expected after the refactoring. Refactor existing code to improve its quality. Break down large, complex functions, eliminate duplicated code, and enhance readability.
Documentation Enhancement
Invest in comprehensive documentation. Clear explanations reduce ambiguity and facilitate maintenance.
Development Practices
Adopt practices like test-driven development (TDD), continuous integration, and pair programming. Train your specialists on how to write a clean code, refactor successfully the code, prepare reusable or automate parts of their work.
Prioritization
Use cost-benefit analysis to prioritize debt repayment. Balance feature development with debt reduction. Here the TDR ratio can help a lot, having in mind that if later we will start the repayment that the ration should be higher. Once the dept will be repaid we can lower down the ratio, but it should never be close to zero or even zero.
Ultimately, managing technical debt is not solely about managing or repaying it. It starts with a clear definition of what constitutes technical debt for your team and an understanding that it’s an ongoing process. It’s about striking a balance between moving fast to deliver new features and taking the time to maintain the quality and integrity of the codebase.
Preventing Technical Debt
Preventing technical debt is about taking proactive measures to ensure the long-term health of a software project. This involves establishing good coding practices, prioritizing quality over speed, and making informed decisions that consider future implications.
Prevention starts with education. Teams and project stakeholder should be aware of what technical debt is and the impact it can have on their work. From there, it’s about integrating practices that reduce the likelihood of debt piling up. This includes adhering to coding standards, performing regular code reviews, and automating testing wherever possible.
Another key aspect is design. Thoughtful system architecture and design can prevent a multitude of problems down the line. It’s about choosing the right patterns, frameworks, and technologies that will stand the test of time and adapt to changing requirements.
Communication is crucial. Teams should discuss potential technical debt openly and make collective decisions on how to handle it. This collaborative approach ensures that everyone is aligned and working towards the same goal: a clean, efficient, and maintainable codebase.
In essence, preventing technical debt requires foresight, discipline, and a commitment to quality. It’s an investment in the future of the software and, ultimately, the success of the business.
