Types & Causes the Technical Debt

Introduction

Technical debt is the hidden cost of speed in software development - impacting efficiency, scalability, and maintainability. But what if managing it could become a competitive advantage?

This article dives into the different faces of technical debt - architecture, code, and infrastructure - and uncovers the root causes, from the pressure to deliver fast to reliance on outdated technologies. Understanding these challenges isn't just about damage control; it’s about future-proofing your systems. By tackling technical debt head-on, organizations can build stronger, more sustainable solutions that stand the test of time.

Types of technical debt

Technical debt comes in different forms, each with unique characteristics and implications.

Architecture debt: Often named as the most damaging type of tech debt, refers to compromises or suboptimal decisions made at a system's architectural level. It might involve using outdated technologies, creating overly complex structures, or neglecting scalability concerns. Architectural debt can be particularly costly as it often requires significant refactoring or a complete system redesign.

Code debt: This is perhaps the most common type of technical debt and encompasses many issues within the code. It might involve poorly written or convoluted code, lack of proper documentation, or insufficient testing.

Code debt consumes development time and can lead to increased maintenance efforts, a higher likelihood of bugs, and difficulty adding new features and vulnerabilities at the lowest level.

Design debt: This relates to shortcomings or inconsistencies in the design of the software. It might involve poor user interface design, inadequate error handling, or lack of modularity. Design debt can impact user experience, system reliability, and the ability to adapt to changing requirements.

Documentation debt: This refers to the lack of or outdated documentation for a software system. According to Stack Overflow's Developer Survey, 54% of developers report working with inadequate documentation, which can make it difficult for new developers to understand the codebase, increase onboarding time by up to 60%, and hinder maintenance efforts. SME's are often the bottleneck as teams rely on top engineers to understand existing code functionality, context and architecture. Supporting the navigation of applications from the infrastructure, architecture, code and dependencies and making sure it’s always reflective of the truth and up to date is a significant challenge in itself.

Infrastructure debt: This type of debt relates to the underlying infrastructure on which the software runs. It might involve outdated hardware, misconfigured servers, or neglected security updates. Infrastructure debt can lead to performance issues, security vulnerabilities, and downtime but also block or prevent initiatives such as leveraging optimal cloud compute technologies and software delivery methodologies. Flexera's State of the Cloud Report indicates that 47% of organizations cite infrastructure modernization as their top challenge and it’s one that never fades as the pace of cloud-native continues to evolve, often too fast to keep up with.

Test debt: This occurs when insufficient testing or outdated test suites are in place. It can lead to undetected bugs, regressions, and a lack of confidence in deploying new code.

Understanding the different types of technical debt helps identify and prioritize improvement areas. It also allows for more informed decision-making when weighing the short-term benefits of shortcuts against the long-term costs of accumulating debt.

types-causes-schema"

Common causes and contributing factors

Let's break down some of the most frequent offenders:

Pressure to deliver quickly: The demand for faster time-to-market can lead to shortcuts and compromises in the development process. DevOps Research shows that 73% of organizations report pressure to release features faster as a primary contributor to technical debt. Rushing to meet deadlines often results in code that's less than ideal, tests that are skipped, and documentation that's incomplete or non-existent and the same pressure moves teams on to the next task, failing to go back and maintain effectively and continuously.

Lack of precise requirements or shifting priorities: Ambiguous or constantly changing requirements can lead to rework and a system that struggles to adapt to evolving business needs. Manual processes and tooling struggles to allow outcomes to be achieved in the timelines required.

Inadequate testing: Insufficient testing can allow bugs and vulnerabilities to slip through the cracks. According to Tricentis, organizations with inadequate test coverage spend 3x more time on bug fixes post-release.

Lack of technical expertise or experience: Inexperienced developers might inadvertently introduce technical debt due to a lack of understanding of best practices or design patterns. Stack Overflow's survey reveals that teams with junior-heavy compositions contribute up to 40% more technical debt unknowingly.

Outdated technologies or frameworks: Relying on obsolete technologies or frameworks can lead to maintenance challenges, compatibility issues, and security vulnerabilities. Forrester reports that 42% of companies cite outdated technology stacks as their primary source of technical debt. Legacy or antiquated codebases are usually impacted by this type of debt. It’s also a treadmill with popular frameworks upgrading to new versions every 2 years.

Poor communication and collaboration: When software development teams don't communicate effectively or collaborate efficiently, it can lead to misunderstandings, duplicated efforts, and inconsistent code. McKinsey found that teams with poor collaboration practices accumulate technical debt 2.5x faster than those with strong communication protocols. One of the obvious manifestations of tech debt is poorly written and maintained documentation of the code, the software bill of materials and the system itself architecturally. High levels of comprehension across teams helps to prevent ramp up in addressing change or evaluating applications.

Conclusion

Managing technical debt is more than a cleanup task - it's a strategy for long-term success. It calls for a proactive mindset: fostering clear communication, maintaining solid documentation, conducting regular testing, and staying ahead of tech trends.

By recognizing the types of debt and their root causes, teams can shift from reactive fixes to strategic improvements, reducing risks and paving the way for smoother development. While technical debt often comes with the territory in fast-paced environments, systematically tackling it leads to better performance, lower costs, and the agility to thrive in an ever-changing landscape.