1. INTRODUCTION

While software developers are often familiar with the term “technical debt,” the concept is less understood by those outside the profession. However, understanding technical debt and its short- to long-term implications is essential for businesses and anyone involved in the software industry, including solution architects, developers, project and product managers, software testers, and business stakeholders. This article will explore technical debt, its causes, impacts, and strategies for managing it.

What is technical debt?

Ward Cunningham first introduced the term “technical debt” in 1992. He described it as the internal tasks that are deferred during development, which, if not addressed, could lead to future problems. More recently, the term has been used to describe various issues throughout the software development life cycle, including those that negatively affect deployment activities, system upgrades or evolution, and any obstacles hindering development efforts’ progress.

In simple terms, technical debt is a metaphor that compares the shortcuts or compromises made during software development to financial debt. These shortcuts or compromises can result in increased costs, slower growth, and reduced productivity in the future.

The metaphor is apt: just as taking on financial debt provides short-term resources but incurs future costs when the debt must be repaid, technical debt offers immediate benefits at the cost of potential future challenges.

  1. TYPES OF TECHNICAL DEBT

The two major categories of technical debt are intentional and unintentional.

Intentional Technical Debt: This debt is taken consciously or strategically to refactor later and must be properly documented.  A major factor for this is urgency, where there is a tight schedule or pressure from managers to deliver features quickly.

Unintentional Technical Debt:  This is a non-strategic debt resulting from doing a poor job without plans to refactor the code. This can also happen due to a lack of experience, poor design decisions, or rapidly evolving product requirements.

The paper Towards an Ontology of Terms on Technical Debt cites 13 different types of technical debt with key indicators for each.

  1. Architectural Debt refers to the problems encountered in project architecture, such as violation of modularity, which can affect architectural requirements (performance, robustness, among others).
  2. Build Debt: Refers to build-related issues that make this task harder, and more time/processing consuming unnecessarily.
  3. Code Debt: Refers to the problems found in the source code which can negatively affect the legibility of the code making it more difficult to maintain.
  4. Defect Debt: Refers to known defects, usually identified by testing activities or by the user, that the change control board agrees should be fixed, but have been deferred due to competing priorities and limited resources.
  5. Design Debt: This refers to debt that can be discovered by analyzing the source code and identifying the use of practices that violate the principles of good object-oriented design (for example, very large or tightly coupled classes).
  6. Documentation Debt: Refers to the problems found in software project documentation, which can be identified by looking for missing, inadequate, or incomplete documentation. 
  7. Infrastructure Debt: Refers to infrastructure issues that, if present in the software organization, can delay or hinder some development activities. Some examples of this kind of debt are delaying an upgrade or infrastructure fix.
  8. People Debt: Refers to people issues that, if present in the software organization, can delay or hinder some development activities. An example of this kind of debt is expertise concentrated in too few people, as an effect of delayed training and/or hiring.
  9. Process Debt: Refers to inefficient process
  10. Requirement Debt: Refers to the gap between the optimal requirement specification and the actual system specification.
  11. Service Debt: Refers to inappropriate web services that lead to incompatibility between service features and application requirements.
  12. Test Automation Debt: Refers to the work involved in automating tests of previously developed functionality to support continuous integration and faster development cycles.
  13. Test Debt: Refers to issues found in testing activities that can affect testing activities’ quality.
  1. COMMON CAUSES OF TECHNICAL DEBT
  • Business Pressure & Time constraints: When the business needs to ship features fast, developers are often under pressure to meet tight deadlines and in the process, tend to focus on delivery rather than code quality. They prioritize speed over quality and incur technical debt.
  • Evolving Requirements: When requirements are ever-evolving, the codebase is frequently updated. With these rapid changes comes the likelihood of doing a poor job, potentially making older code inefficient and outdated, which can lead to technical debt.
  • Lack of Skilled Talents: Inexperienced developers or lack of expertise in certain areas or chosen design patterns, and frameworks can lead to suboptimal code, leading to technical debt.
  • Poor Planning and Documentation: Careful planning and design of a system with adequate documentation ensures that certain approach is followed and knowledge is easily shared among teams, but lack of it can lead to unintended technical debt. Embarking on a project without planning and proper documentation can lead to a codebase that is difficult to maintain.
  • Lack of Standards and Framework: The absence of defined standards within a development team can create significant challenges throughout the entire software development life cycle, ultimately leading to technical debt. 
  • Lack of Issues Tracking and Reviews: When there is a lack of high-quality issue tracking and code reviews, the chances of having technical debt are very high. 
  • Outsourced Software Developers: When resources are outsourced to third-party developers without measures to manage technical debt, it sometimes culminates in the in-house development team needing to refactor the code delivered.
  1. IMPACT OF TECHNICAL DEBT
  • Buggy and unstable production environment: At a level of technical debt, developers deal with bug fixes and an unstable and unreliable production environment. Fixing one bug can introduce new ones, leading to inconsistency in code and data.
  • Decrease in team velocity and productivity: Technical debt often reduces team velocity and extends the time required for code commits, integration, testing, and deployment, ultimately impacting productivity. 
  • Increased cost: Technical debt often results in higher maintenance costs, as addressing issues requires more time and resources. Moreover, the longer technical debt stays unaddressed, the more costly it becomes to resolve. Sometimes, a total redesign and a new implementation are required.
  • Increase in change failure rate: Teams will experience a longer mean time to recovery—the time it takes to restore service—and a higher change failure rate, where deployments to production more frequently result in incidents.
  • Employee morale: Working in a codebase burdened with technical debt can frustrate developers, leading to burnout and lowered morale. This, in turn, can negatively affect team cohesion and productivity. 
  1. IDENTIFYING TECHNICAL DEBT

Efficient management of technical debt requires the ability to identify it.

  • Metrics and Tools: One of the best ways of identifying technical debt is by using code metrics. Static code analysis tools play a crucial role in identifying technical debt by automatically scanning the codebase for issues such as coding standard violations, complex code structures, and potential bugs that compromise code quality, maintainability, reliability, and security. Static code analysis tools provide detailed reports and pinpoint specific areas for improvement, enabling developers to make informed decisions on where to focus their refactoring efforts, which helps manage and reduce technical debt over time.
  • Code Reviews: Regular code reviews make effective the ability to identify technical debt, enabling teams to spot and address issues early before they become deeply embedded in the codebase.
  • Issue Trackers: Keeping a thorough issue-tracking system helps identify problematic areas in the code that may signal deeper technical debt issues.
  • Developer Feedback: Often, the most reliable indicators of technical debt come from the developers themselves. Regular meetings or feedback sessions can reveal parts of the codebase that are challenging to work with or maintain.
  1. HOW TO MANAGE AND MITIGATE TECHNICAL DEBT
  • Automated testing, Code reviews, and Audits: Code reviews, automated testing, and regular audits can effectively highlight technical debt. Teams should proactively seek out technical debt and identify areas for improvement, focusing on solutions rather than assigning blame.
  • Establishing Debt Management Process: Implementing a structured approach to managing technical debt is crucial for teams to prioritize and tackle it efficiently. This can be achieved by allocating time for debt repayment during each sprint and dedicated debt tracking – maintaining a separate backlog or register to track technical debt, enabling transparent monitoring and prioritization.
  • Balancing Speed and Quality: Striking a balance between timely delivery and code quality is crucial. Although incurring technical debt may be necessary to achieve business objectives, it’s vital to have a clear strategy for repaying that debt to avoid long-term consequences. By prioritizing deadlines and code maintainability, teams can ensure a sustainable pace of development and minimize the risk of accumulated debt.
  1. CASE STUDY

BACKGROUND

A company wants to rebuild and extend the functionalities of an existing legacy application used to manage contract employees and decides to outsource the work to external developers. They assembled a team consisting of a product owner, a scrum master, subject matter experts, an in-house lead engineer, and a team of external developers. The primary goal was to rapidly deploy an MVP with more functionalities than the existing legacy application, using Agile methodologies.

Code templates were given to the external developers to ensure adherence to standards 

during development.

  1. CONCLUSION

In agile environments where progress is measured by working software and startups where products need to ship fast, technical debt is used as a tool to get ahead and may not necessarily be a bad thing. However, if they aren’t documented properly with a technical debt management plan as the codebase continues to grow, it may pose a big problem.

Generally, while technical debt is inevitable, with proper mitigation and management processes, it shouldn’t be a roadblock. 

Engineering teams and stakeholders should ensure the right tools are deployed to deal with the most common debt, code debt, while also ensuring that other types are given the appropriate attention.