Technical Debt
Technical debt (technical debt) describes the hidden cost of taking shortcuts in software development – at the expense of long-term code quality.
Technical debt is the invisible weight that slows software projects over time. Like financial debt it accrues interest: what saves a few hours today can cost days or weeks later. Every project has technical debt – the question is whether it is managed consciously or left to grow.
What is Technical Debt?
Technical debt is a metaphor coined by Ward Cunningham in 1992. It describes the extra cost that arises when quick, suboptimal solutions are chosen instead of clean, sustainable ones. Examples: copied instead of abstracted code, missing tests, outdated dependencies, poor documentation or architecture that grew instead of being designed. Technical debt is not always bad – deliberate debt (e.g. for fast market entry) can be strategic but must be paid down. Unconscious or ignored debt leads to rising complexity, lower productivity and team frustration.
How does Technical Debt work?
Debt accumulates through time pressure, lack of code review, outdated dependencies and new requirements stacked onto architecture that was not designed for them. The interest shows up in longer development times for new features, more bugs, longer onboarding and more testing. Tools like SonarQube can quantify technical debt and estimate effort to pay it down.
Practical Examples
A startup built its MVP under pressure in 3 months. Two years later every new feature takes three times longer because the code is messy and untested.
An e-commerce platform uses an old PHP version. Security patches are no longer available and migration gets more expensive with each month of delay.
A team copies logic instead of abstracting it: one bug has to be fixed in 12 places – and is missed in 3.
A monolith cannot scale parts independently: the database layer slows the whole app even though only one module is under load.
Typical Use Cases
Debt inventory: Teams measure technical debt with tools like SonarQube and create a paydown plan
Refactoring sprints: Regular sprints dedicated only to reducing technical debt
Architecture modernisation: Legacy systems gradually migrated to modern architecture
Boy Scout Rule: Developers leave every area of code a bit better than they found it
Definition of Done: Code quality metrics (coverage, linting, no new debt) as mandatory criteria
Advantages and Disadvantages
Advantages
- Conscious technical debt can be strategic: fast market entry, proof of concept, time-critical features
- The metaphor helps explain technical issues to non-technical stakeholders
- Measurable metrics allow objective prioritisation of paydown
- Paying down debt improves team satisfaction, productivity and quality in the long run
Disadvantages
- Uncontrolled debt slows development exponentially and frustrates the team
- Paydown competes with feature work for budget and management attention
- Hard to measure: Total technical debt is often only roughly known
- Hidden risks: Security issues in old dependencies often only surface when something goes wrong
Frequently Asked Questions about Technical Debt
How do you measure technical debt?
How do you get management to invest in paying down debt?
Can you avoid technical debt completely?
Related Terms
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