Managing Technical Debt in Software Development
Recognize risks, ensure quality
Technical debt arises when short-term solutions in software development remain in place permanently. What brings speed today increases maintenance costs, complexity, and risk tomorrow. Those who make technical debt visible at an early stage and actively manage it ensure long-term quality and development speed.
Technical Debt in Code: Risk or Control Instrument?
Imagine a new feature has to be implemented under significant time pressure. The solution works and goes live quickly - at first, everything seems fine. But a few weeks later, bugs start to pile up, changes take longer, and new developers struggle to understand the code.
These situations are part of everyday life in modern software development. This is precisely where technical debt comes into play in practice.
Technical debt - often referred to as technical debt - does not arise by chance. It results from conscious or unconscious decisions during the development process. For dev leads, engineering managers, and CTOs, technical debt is not destiny. It can be recognized, evaluated, and reduced in a targeted manner - provided it is made transparent and actively managed.
What Is Meant by Technical Debt - And What Is Not
Technical debt refers to the additional effort required when quick or straightforward solutions replace sustainable architecture or code quality standards in the short term. Typical triggers in software development are missing or insufficient tests, high time pressure due to business priorities, skipped code reviews, or historically evolved architectures.
In the short term, technical debt can accelerate delivery. In the long term, it affects maintainability, stability, and scalability - and therefore the productivity of teams.
It is essential to make a precise classification: technical debt is not bad per se. It can be helpful if entered into consciously. It becomes problematic when it grows uncontrollably and is no longer visible.
Types of Technical Debt
In practice, several forms can be distinguished:
- Code Debt: Complex, difficult to understand, or heavily duplicated code
- Architecture debt: tight couplings or lack of modularity
- Test Debt: missing or insufficient automated tests
- Documentation Debt: incomplete or outdated documentation
This differentiation facilitates targeted evaluation and prioritization.
Making Technical Debt Measurable - Beyond Gut Feeling
To reduce technical debt, it must first be made visible. Subjective assessments are not enough for this. In practice, a combination of direct code metrics and indirect signals from everyday software development helps.
Code quality metrics provide objective indications of structural weaknesses in the code. They show where changes can be particularly expensive, risky, or error-prone:
- Cyclomatic complexity makes visible how nested and difficult to test individual code areas are.
- Code duplication increases maintenance effort, as changes have to be made in multiple places.
- Code smells indicate structural problems that impair maintainability in the long term.
- Architecture dependencies reveal where modules are overly coupled, and changes can have unexpected effects.
Not all technical debts can be read directly from the code. Test and maintenance metrics help to identify the effects of technical debt in day-to-day operations:
- Test coverage shows how well changes are tested.
- The average time to correct errors provides information on how maintainable and comprehensible the system is.
- The ratio of new to existing bugs may indicate deeper structural problems.
- The effort for maintenance compared to the further development of functions illustrates how much development capacity is tied up in existing debts.
If the maintenance effort increases continuously or development cycles are extended, this is usually a clear sign of growing
A technical debt index estimates the effort required to fix technical debt relative to the system size or the total development effort. The absolute value is less important than its development over several releases.
Additional transparency is created when teams systematically record technical debts in the backlog. If they are managed as separate tickets, they can be prioritized, planned, and consciously integrated into roadmaps - instead of being permanently suppressed.
Tools for Support
Without suitable tools, technical debt management often remains abstract. Tools help to create structure and transparency.
Static code analysis tools such as SonarQube make code smells, duplicates, test coverage, and security gaps visible. The technical debt value derived from this provides an initial estimate of the remediation effort.
CodeScene complements this view by combining code analysis with insights from teamwork. This makes it possible to identify particularly high-maintenance areas, hotspots with a great change frequency, or areas with high risk due to knowledge concentration.
AI-supported pull request reviews, for example, with GitHub Copilot, help teams avoid new technical debt at an early stage. They help to ensure compliance with coding standards and provide feedback on readability and complexity without unnecessarily slowing down the review process.
Project and ticket management tools such as Jira ultimately ensure that technical debt is not only recognized, but can also be planned and systematically reduced across sprints.
Targeted Reduction of Technical Debt: Best Practices
Recognizing technical debt is only the first step. A structured reduction that can be realistically integrated into day-to-day development is crucial. Several approaches have proven successful in practice:
Prioritize technical debt
Not every technical debt is equally critical. Clear prioritization helps deploy limited resources where they will deliver the most significant business and technical benefit. An evaluation based on the following criteria has proven effective:
- Business risk, such as the impact on availability or sales
- Maintenance effort resulting from existing technical debt
- Change the frequency of affected code areas
- Relevance for central product functions
Fixed scheduling of refactoring
Technical debt can only be reduced if time is deliberately set aside for it. Successful teams do not treat refactoring as a secondary task, but as an integral part of planning:
- Fixed capacity share per sprint for technical improvements
- Targeted refactoring days per release
- Own technical stories in the backlog that can be prioritized
Establish quality gates
Quality gates in CI/CD pipelines help to prevent new technical debts from arising in the first place. They make code quality a measurable part of the development process, for example, by:
- Minimum requirements for test coverage
- Defined limit values for complexity
- No new critical code smells
Extend the definition of done
A clearly defined definition of done ensures that short-term solutions do not remain permanently in the code and that necessary documentation is not subsequently forgotten. In practice, this includes the following:
- Automated tests for relevant functionalities
- Documentation of central architectural decisions and relevant functions
- Completed code reviews
Transparency towards business stakeholders
Technical debt is not a purely technical issue. If their effects on time-to-market, stability, and costs are made transparent, the willingness to make the necessary investments increases.
Technical debt is unavoidable in software development. The decisive factor is not its existence, but how it is handled.
Those who systematically visualize, evaluate, and continuously reduce technical debt maintain their systems' ability to act. Those who ignore it pay the price in the form of reduced development speed, rising maintenance costs, and increased risk.
Technical debt management is therefore a strategic management task - not a peripheral technical issue.
Frequently Asked Questions and Answers About Technical Debt
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Is technical debt always negative?
No. Deliberately incurred technical debt can make strategic sense, for example, for a quick market launch or to validate a business model. They become critical if they grow uncontrollably and are not actively managed.
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How is technical debt actually created?
Technical debt is often caused by time pressure, missing or insufficient tests, unclear architecture decisions, or skipped code reviews. Historically grown systems also encourage their development.
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How can technical debt be prioritized?
The prioritization is based on clear criteria such as business risk, maintenance effort, change frequency of affected components, and their system criticality.
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How can you recognize growing technical debt?
Typical signs include increasing error rates, longer development cycles, a higher proportion of maintenance, and slower development speed.
Written by
Peter Chojecki is an IT manager specializing in software development and cloud-based portal solutions. With a passion for modern architecture concepts, DevOps and scalable cloud technologies, he designs future-proof platforms that combine user-friendliness and technical excellence. His focus is on the further development of digital ecosystems in which efficiency, security and innovation go hand in hand.