What is the cost of Technical Debt?

Technical debt is a term used to describe the cost associated with maintaining and improving a codebase over time. This cost can be high, as it often involves fixing issues, improving performance, and updating the code to meet changing requirements and industry standards. While technical debt is a normal part of the software development process, it can become a major problem if it is not managed properly.

What is technical debt?

Technical debt refers to the cost associated with maintaining and improving a codebase over time. This can include fixing bugs and other issues, improving performance, and updating the code to meet changing requirements and industry standards.

Technical debt is a normal part of the software development process, as it is impossible to anticipate and address every potential issue or requirement upfront. However, if technical debt is not managed properly, it can become a major problem, as it can lead to delays, increased costs, and reduced quality of the code.

Causes of technical debt

There are many different causes of technical debt, including:

• Short-term thinking: Technical debt often arises when developers prioritize short-term gains over long-term sustainability. For example, if a developer takes a shortcut to meet a tight deadline, this can create technical debt that will need to be addressed in the future.
• Lack of planning: Technical debt can also be caused by a lack of planning and foresight. If developers do not adequately plan for the long-term maintenance and improvement of the codebase, this can lead to technical debt as the codebase grows and changes over time.
• Changing requirements: Technical debt can also be caused by changes in requirements or industry standards. If the code is not regularly updated to meet these changes, it can become outdated and difficult to maintain, leading to technical debt.

The impact of technical debt

The impact of technical debt can be significant, as it can lead to delays, increased costs, and reduced quality of the code. Some of the specific impacts of technical debt include:

• Increased costs: Technical debt can increase the cost of maintaining and improving the codebase over time. This can include the cost of fixing issues and improving performance, as well as the cost of lost productivity due to delays and other issues.
• Reduced quality: Technical debt can also lead to a reduction in the overall quality of the code. As the codebase becomes more complex and difficult to maintain, it can be more prone to bugs and other issues, which can impact the user experience and overall functionality of the software.
• Delays: Technical debt can also lead to delays in the development process, as developers may need to spend more time fixing issues and addressing other aspects of the codebase. This can impact the ability to meet deadlines and can delay the release of new features and updates.

A Stripe study from 2018 estimates that developers waste 40% of their time because of bad code and technical debt.

Best practices for managing technical debt

Managing technical debt is an important part of the software development process, and there are several best practices that can help ensure that it is managed effectively. These include:

• Prioritizing long-term sustainability: Developers should prioritize long-term sustainability when making decisions about the codebase, rather than focusing solely on short-term gains. This can help prevent the accumulation of unnecessary technical debt.
• Regularly reviewing and refactoring the code: Regularly reviewing and refactoring the code can help identify and address technical debt early on. This can include identifying and fixing issues, improving performance, and updating the code to meet changing requirements and industry standards. You can use static code analysis to detect coding issues.
• Involving the entire development team: Managing technical debt is not just the responsibility of individual developers – it should be a team effort. Codiga helps you to analyze your team behavior and detect potential bottlenecks.