10 Common Technical Debt Examples with Solving Guidance and Tips on How to Avoid

Last updated on
October 6, 2023


Tech debt examples

  • Legacy Code
  • Insufficient Testing
  • Hard-coded Values
  • Outdated Libraries or Dependencies
  • Lack of Documentation
  • Suboptimal Architecture
  • Inconsistent Coding Standards
  • Deferred Upgrades
  • Tightly Coupled Components
  • Accumulated Bug Debt


10 Common Technical Debt Examples with Solving Guidance and Tips on How to Avoid

Software development shortcuts

In the world of software, we sometimes take shortcuts to get things done faster. These shortcuts, known as "technical debt," can pile up and make future work harder, much like unpaid bills. In this article, we'll explore different types of technical debt, why they happen, and how to handle them. Think of it as a guide to keeping your software projects clean and efficient. Let's dive in and learn how to avoid these common pitfalls!

1. Legacy Code

  • Explanation: Legacy code refers to old code that is no longer in line with current best practices or technologies but is still in use.
  • Reasons: It often arises from rapid development cycles, lack of documentation, or changes in team members.
  • Seriousness: Very serious, as it can hinder future development and can introduce security vulnerabilities.
  • Consequences: Increased maintenance costs, potential security risks, and decreased agility in implementing new features.
  • How to Spot It: Parts of the codebase that are rarely touched or understood by the current team, or areas where updates are avoided due to fear of breaking things.
  • How to Avoid: Regularly refactor and update the codebase. Invest in continuous training for the team to keep up with current best practices. Encourage a culture of continuous improvement.
  • How to Deal With It: Refactoring, which means restructuring existing code without changing its external behavior. Also, ensuring proper documentation and tests for the legacy code.
  • Example: Many banking systems still run on old mainframe systems written in COBOL. These systems are costly to maintain and difficult to integrate with modern technologies.

2. Insufficient Testing

  • Explanation: This refers to software that has been released with minimal testing or without comprehensive test coverage.
  • Reasons: Tight deadlines, lack of resources, or underestimating the importance of testing.
  • Seriousness: Very serious, as it can lead to undetected bugs in production.
  • Consequences: Software malfunctions, security breaches, and loss of customer trust.
  • How to Spot It: Frequent and unexpected bugs in production, lack of automated tests, or areas of the codebase with low test coverage.
  • How to Avoid: Adopt a test-driven development (TDD) approach. Allocate sufficient time for testing in the development cycle. Use automated testing tools and continuous integration to catch issues early.
  • How to Deal With It: Implementing automated testing, continuous integration, and dedicating resources to thorough testing.
  • Example: The 2012 Knight Capital trading glitch was due to untested software, leading to a $440 million loss in just 45 minutes.

3. Hard-coded Values

  • Explanation: Hard-coding refers to embedding specific values directly into the code rather than using variables or configuration files.
  • Reasons: Quick fixes, oversight, or lack of foresight into future changes.
  • Seriousness: Moderate to serious, depending on the nature of the value and where it's used.
  • Consequences: Difficulty in updating or scaling the software, potential security risks if sensitive information is hard-coded.
  • How to Spot It: Direct references to specific values in the code instead of variables or configurations. Code reviews and static code analysis can help identify these.
  • How to Avoid: Use configuration files or environment variables for values that might change. Educate developers about the risks and downsides of hard-coding.
  • How to Deal With It: Refactoring to replace hard-coded values with variables or configuration files.
  • Example: An application that hard-codes database connection details would need to be manually updated and redeployed if the database location changes.

4. Outdated Libraries or Dependencies

  • Explanation: Using old versions of third-party libraries or dependencies that are no longer supported or have known issues.
  • Reasons: Neglecting regular updates, compatibility issues, or lack of awareness of updates.
  • Seriousness: Serious, especially if the outdated libraries have known security vulnerabilities.
  • Consequences: Security breaches, software crashes, or incompatibility issues.
  • How to Spot It: Dependency management tools can notify of outdated libraries. Regular audits of dependencies can also reveal this debt.
  • How to Avoid: Regularly review and update dependencies. Use tools that can automatically check for outdated or vulnerable libraries. Educate the team about the importance of staying updated.
  • How to Deal With It: Regularly reviewing and updating dependencies, using tools to monitor for outdated libraries.
  • Example: The Equifax data breach in 2017 was due to an outdated version of the Apache Struts framework.

5. Lack of Documentation

  • Explanation: Absence of clear documentation for the code, making it difficult for others to understand or modify.
  • Reasons: Tight deadlines, developer oversight, or lack of emphasis on documentation.
  • Seriousness: Moderate to serious, depending on the complexity of the software.
  • Consequences: Slower onboarding of new team members, increased development time, and potential introduction of bugs.
  • How to Spot It: New team members struggling to understand the code, or developers spending excessive time deciphering existing code rather than writing new code.
  • How to Avoid: Make documentation a required part of the development process. Use tools that facilitate documentation, like Doxygen for code or Confluence for architectural decisions. Encourage a culture where documentation is valued.
  • How to Deal With It: Allocating time for documentation, using tools that encourage documentation, and promoting a culture that values documentation.
  • Example: A developer leaving the company without documenting their code can lead to weeks or even months of delay as the new developer tries to decipher the code.

6. Suboptimal Architecture

  • Explanation: The software's architecture doesn't support current or future requirements efficiently.
  • Reasons: Initial architecture was designed for a smaller scale or different requirements, or there was a lack of architectural foresight.
  • Seriousness: Very serious, as it can hinder scalability and performance.
  • Consequences: Performance bottlenecks, difficulty in adding new features, and increased maintenance costs.
  • How to Spot It: Performance bottlenecks, difficulty in scaling, or when adding new features becomes increasingly complex. Regular system reviews and architectural evaluations can also highlight areas of concern.
  • How to Deal With It: Re-architecting or refactoring critical parts of the system.
  • How to Avoid: Invest time in proper architectural planning at the outset of a project. Regularly review and adjust the architecture as requirements evolve. Adopt architectural patterns that are scalable and flexible.
  • Example: A startup that quickly grows its user base might find its initial database architecture can't handle the increased load, leading to slow response times.

7. Inconsistent Coding Standards

  • Explanation: Different parts of the codebase follow different coding styles or standards.
  • Reasons: Multiple developers with different coding habits, lack of defined coding standards.
  • Seriousness: Moderate, as it affects code readability and maintainability.
  • Consequences: Difficulty in understanding and maintaining code, increased chances of bugs.
  • How to Spot It: Code reviews reveal varying coding styles or practices within the same codebase. Tools like linters or static code analyzers can also flag inconsistencies.
  • How to Avoid: Establish and enforce coding standards from the beginning of the project. Use tools like linters and formatters to automatically enforce these standards. Conduct regular code reviews to ensure adherence.
  • How to Deal With It: Implementing and enforcing coding standards, using tools like linters.
  • Example: A project where some developers use tabs and others use spaces for indentation can lead to messy and hard-to-read code.

8. Deferred Upgrades

  • Explanation: Postponing necessary upgrades to the system or infrastructure.
  • Reasons: Concerns about breaking changes, lack of resources, or prioritizing new features over upgrades.
  • Seriousness: Serious, especially if the deferred upgrades contain security or performance improvements.
  • Consequences: Security vulnerabilities, missing out on improved features or performance enhancements.
  • How to Spot It: Regular checks of software and library versions against the latest available versions. Monitoring tools or dependency management tools can notify when updates are available.
  • How to Avoid: Set up a regular schedule for reviewing and updating dependencies. Use automated tools to notify when updates are available. Allocate time in the development cycle specifically for upgrades.
  • How to Deal With It: Scheduling regular upgrade cycles, having a rollback plan in case of issues.
  • Example: A company that defers operating system upgrades might be exposed to security vulnerabilities that were patched in newer versions.

9. Tightly Coupled Components

  • Explanation: Components or modules of the software are too interdependent, making changes in one component affect others.
  • Reasons: Lack of modular design, overlooking the principles of separation of concerns.
  • Seriousness: Serious, as it affects maintainability and scalability.
  • Consequences: Difficulty in making changes, increased testing efforts, and potential for more bugs.
  • How to Deal With It: Refactoring to ensure components are loosely coupled, following design principles like SOLID.
  • How to Spot It: Changes in one module frequently cause unexpected issues in another. Code reviews and architectural evaluations can also identify areas where components are overly interdependent.
  • How to Avoid: Design with modularity and separation of concerns in mind. Follow design principles like SOLID. Use design patterns that promote loose coupling.
  • Example: Changing a feature in one module of an e-commerce platform causes unexpected bugs in the payment processing module due to tight coupling.

10. Accumulated Bug Debt

  • Explanation: Known bugs or issues are not addressed and keep accumulating.
  • Reasons: Prioritizing new features over bug fixes, lack of resources, or underestimating the impact of bugs.
  • Seriousness: Can range from moderate to very serious, depending on the nature of the bugs.
  • Consequences: Degraded user experience, potential data loss, or system crashes.
  • How to Deal With It: Prioritizing critical bug fixes, allocating dedicated time for addressing known issues.
  • How to Spot It: A growing backlog of known, unresolved bugs. Regularly reviewing bug tracking systems and listening to user feedback can highlight this debt.
  • How to Avoid: Prioritize fixing critical bugs over adding new features. Allocate dedicated time in each sprint or development cycle for addressing known issues. Use bug tracking tools effectively.
  • Example: A software with known performance issues might lose users to competitors if those issues are not addressed in time.

How to Avoid Tech Debt

Fostering a Culture of Continuous Learning

Importance: The tech industry is ever-evolving. New tools, methodologies, and best practices emerge regularly. If teams don't keep up, they risk using outdated methods that can lead to technical debt.

Implementation: Encourage team members to attend workshops, webinars, and conferences. Allocate time for self-learning and exploration. Share knowledge within the team through regular tech talks or knowledge-sharing sessions.

Regular Reviews

Importance: Regularly reviewing code, architecture, and processes helps identify potential areas of technical debt before they become significant issues. It ensures that the team is aligned and that the codebase remains maintainable.

Implementation: Conduct code reviews for every piece of code before it's merged. Hold architectural review meetings to discuss and evaluate system design decisions. Periodically review and refine development processes to ensure they're effective.

Proactive Planning

Importance: Proactively planning for future requirements can prevent hasty decisions that lead to technical debt. It's about foreseeing potential challenges and preparing for them.

Implementation: Spend time understanding the project's long-term vision and goals. Design systems that are scalable and flexible. Anticipate changes in user requirements or technology landscapes and plan accordingly.

Striking a Balance Between Moving Fast and Ensuring Quality

The Dilemma: Startups and tech companies often operate under the mantra "move fast and break things." While speed is essential, especially in competitive markets, it shouldn't come at the expense of quality. Rushed decisions or shortcuts can lead to significant technical debt.

Finding the Balance: It's essential to prioritize tasks effectively. Not everything needs to be perfect, but critical components, especially those related to security, scalability, and user experience, should not be compromised. Implementing agile methodologies can help teams iterate quickly while maintaining a focus on quality. Feedback loops, both from users and internal teams, can provide insights into where the balance currently stands and where adjustments are needed.

Tech debt: what you can do now

Technical debt, often likened to financial debt, refers to the long-term costs and consequences of shortcuts or suboptimal decisions made during software development. While some technical debt is inevitable, especially in fast-paced environments, it can accumulate and become a significant burden if not addressed. Examples of technical debt include legacy code, insufficient testing, hard-coded values, outdated libraries, and more. Recognizing, managing, and avoiding technical debt requires a blend of continuous learning, regular reviews, proactive planning, and striking a balance between speed and quality.

Your next steps can be:

  • Self-Assessment: Review your current projects or systems to identify areas of potential technical debt. Tools like static code analyzers, dependency checkers, and architectural review frameworks can assist in this process.
  • Prioritize and Address: Not all technical debt is equal. Prioritize addressing those that have the most significant impact on security, user experience, and future development.
  • Educate the Team: Organize workshops or training sessions on best practices, the importance of documentation, and the dangers of accumulating technical debt.
  • Implement Regular Reviews: Schedule regular code and architectural reviews. Consider adopting methodologies like Agile or Scrum that emphasize iterative development and continuous feedback.
  • Stay Updated: Keep abreast of the latest in software development practices, tools, and methodologies. Encourage a culture of continuous learning within the team.
  • Seek External Input: Sometimes, an external perspective can provide fresh insights. Consider periodic audits or consultations with external experts to get an unbiased view of your technical debt situation.

Iterate and Improve: Addressing technical debt is not a one-time activity. Continuously monitor, address, and learn from past decisions to ensure a sustainable and efficient development process.

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Olga Gierszal
Software Engineering Editor

Software development enthusiast with 6 years of professional experience in the tech industry.

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