How to prioritize and manage technical debt


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How to prioritize and manage technical debt


15 Jun 2023


Marta Zwierz

Marta Zwierz

Technical debt is a term used to describe the accumulation of technical challenges and inefficiencies that arise over the course of software development. As software systems grow more complex and requirements change, technical debt can accrue, leading to slower development, reduced quality, and increased risk. This accumulated debt can be compared to financial debt, where the cost of borrowing money increases over time. Similarly, technical debt can accumulate interest as more changes are made to the software.

Importance of managing technical debt

Tech debt's stifling grip on innovation is acknowledged by a notable 90% of IT leaders, as highlighted in a Vanson Bourne survey. In tandem, tech debt's interference with adaptability to shifting business demands is a concern for 88% of developers. Another survey by IDG revealed that, for IT executives, tech debt soared to the second most critical issue, with 86% of the 400 participants citing its impact in the preceding 12 months.

Furthermore, the COVID-19 pandemic has highlighted the importance of agile software development and the need for organizations to be able to adapt quickly to changing circumstances. This has further increased the importance of managing technical debt effectively.

Types of technical debt

Before identifying technical debt, it is important to understand the different types that exist. Technical debt can be classified into four types:

  1. Design debt - occurs when the design of a system or codebase does not adequately support the required functionality or is overly complex.
  2. Code debt - arises when the codebase has issues like outdated programming practices, lack of documentation or consistency, and poor code quality.
  3. Infrastructure debt - arises when the infrastructure supporting a codebase or system is outdated or insufficient.
  4. Testing debt - occurs when testing processes are inadequate or incomplete, leading to bugs or issues not being caught early.

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Signs of technical debt

Technical debt can be difficult to identify as it is often hidden, and its effects are not immediately apparent. Signs of technical debt include:

  • Increased time and cost to make changes or introduce new features
  • Inability to meet the desired performance, reliability, or scalability of the system
  • Growing bug count and customer complaints
  • Codebase complexity and difficulty in understanding code
  • Outdated infrastructure that requires constant maintenance

Tools for identifying technical debt

Various tools are available for identifying technical debt, including:

  1. Code analysis tools - Utilize static code analysis tools like SonarQube, CodeClimate, or ReSharper. These tools help in identifying code smells, security vulnerabilities, and maintainability issues.
  2. Version control systems - Use version control systems like Git, Mercurial, or SVN. These tools allow developers to keep track of code changes, which can be helpful in understanding how technical debt has accumulated over time.
  3. Issue tracking tools - Implement issue-tracking tools like Jira, Trello, or Asana to track technical debt items. These tools allow for the creation of a backlog of technical debt items, which can then be prioritized.
  4. Documentation and knowledge bases - Maintain proper documentation of the codebase and architectural decisions. Confluence and GitHub Wiki are good tools for this. This can help in understanding the origins and implications of technical debt.
  5. Code review tools - Leverage code review tools like Gerrit, Crucible, or built-in features of GitLab and GitHub. Code reviews are essential for preventing new technical debt and catching issues early.
  6. Refactoring tools - Utilize refactoring tools that are integrated into IDEs like Eclipse, IntelliJ IDEA, or Visual Studio. These tools help to improve and streamline the code structure.
  7. Technical debt identification tools - Tools like Sonargraph or CAST highlight portions of the code that contribute the most to technical debt, making it easier to know where to focus your efforts.
  8. Test automation tools - Invest in test automation using tools like JUnit, Selenium, or TestNG. Automated tests are vital for ensuring that changes to the codebase (such as refactorings) don’t introduce new bugs.
  9. CI/CD tools - Implement CI/CD tools like Jenkins, Travis CI, or CircleCI. These tools help in automating the build and deployment processes, and they can also be integrated with code analysis tools to ensure code quality.
  10. Dependency management tools - Tools like Dependabot, Renovate, or Snyk help manage the dependencies of your project. Keeping dependencies up-to-date is an important aspect of managing technical debt.

Criteria for prioritizing technical debt

Managing technical debt can be overwhelming, especially for organizations that have accumulated a lot of it. Prioritizing technical debt is a crucial step in managing it effectively. One of the first things that need to be done is to establish criteria for prioritizing technical debt. The following are some criteria that can be used:

  • Impact on business operations
  • Frequency of occurrence
  • Severity of the problem 
  • Cost of fixing the problem
  • Age of the problem
  • Risk of future problems

technical debt

The Eisenhower Matrix as a tool for prioritizing technical debt

The Eisenhower Matrix is a prioritization tool that can be used to manage technical debt effectively. This matrix, also known as the Urgent-Important Matrix, is a simple but powerful decision-making tool that helps individuals and organizations to prioritize tasks based on their level of urgency and importance.

The matrix is divided into four quadrants:

  • Urgent and important: These tasks require immediate attention and should be dealt with as soon as possible.
  • Important but not urgent: These tasks are important but can be scheduled for a later time.
  • Urgent but not important: These tasks are urgent but can be delegated to someone else.
  • Not urgent and not important: These tasks are low-priority and can be eliminated or postponed.

By using this matrix, your team can prioritize tasks related to technical debt based on their urgency and importance. For example, urgent and important tasks such as security updates should be given top priority, while important but not urgent tasks such as system upgrades can be scheduled for a later time.

Refactoring vs. rewriting code

Once you have prioritized your technical debt, it's time to manage it. One of the first decisions you need to make is whether to refactor or rewrite the code. Refactoring involves making small improvements to the code, while rewriting involves starting from scratch. Refactoring is usually the better option if the code is still usable, and rewriting is necessary only if the code is too outdated and obsolete to salvage.

Technical debt management plan

Managing technical debt requires a plan. A technical debt management plan should be created to outline the steps required to address technical debt. This plan should include the prioritized list of technical debt, who will be responsible for addressing it, and the timeframe for addressing it. The plan should also outline how much time and resources will be allocated to addressing technical debt versus developing new features.

Communication with stakeholders

Managing technical debt also requires clear communication with stakeholders. It's important to communicate the impact of technical debt on the product or project, as well as the benefits of addressing it. Additionally, stakeholders need to understand the trade-offs between addressing technical debt and developing new features. It's important to keep stakeholders informed about progress in addressing technical debt and the impact on the project timeline.

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Navigating tech debt

Managing technical debt is essential in safeguarding software quality and avoiding project setbacks. With the ever-evolving nature of software development, technical debt remains a prominent challenge for many organizations.

It’s imperative to identify types of technical debt, recognize its symptoms, and employ suitable tools for detection and prioritization based on system impact, business risks, and customer effects. Utilizing the Eisenhower Matrix may facilitate balancing technical debt resolution with feature development.

Selecting the appropriate method, be it refactoring or rewriting code, and devising a comprehensive technical debt management plan is fundamental. Moreover, transparent communication with stakeholders is crucial.

Technical debt will persist as a critical concern. As software development metamorphoses, staying proactive in managing technical debt is paramount for the continued success of software ventures.


15 Jun 2023


Marta Zwierz

Marta Zwierz

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