technical debt and how to measure it

In an ideal world, every project is finished on time and within the estimated budget; even better, the budget has allowed us to develop additional features and test everything one more time before the release. In the real world, the development process can encounter several difficulties, and tech debt is among the most common issues the project may face. It is essential to understand what is technical debt, how to measure technical debt, and especially how to tackle it.

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Tech debt is the additional work needed to complete software development. But this notion does not refer solely to the projects that are in development. This issue often follows projects that have been in production for some time. This may be anything, like some module written on the legacy technology, that holds the project back from including a new functionality or influences overall software stability. In this particular case, it can be calculated as the time or money needed for the refactoring of this module’s code or porting it to the new technology. But usually, it is never that simple, and the software system includes a number of drawbacks that can be included in the tech debt of the project.

Not addressing these debts as soon as possible can lead to others in the future, resulting in poor software performance, difficulty or even impossibility in bringing change to the software, and an increased risk of breaking the software after each update. Managing technical debt at an early stage of the development process is crucial.

What is technical debt?

Technical debt outlines the long-term consequences of taking shortcuts or making compromises in software development. It can accumulate over time and negatively impact software quality, productivity, and development costs. Therefore, it is important for development teams to understand the concept of technical debt and take measures to prevent or manage it.

The use of the term is a reference borrowed from the finance world, like financial or tech debts. If they are not resolved very quickly, it can generate interest. In other words, it can give rise to new tech debts and can cost a lot to the software owner and development team.

Now that we know what is technical debt, it is important to know how we get it.


To better address this topic, it is essential to understand what caused them in the first place. There are four major reasons: 

Poor conception: When developing an application, the speed at which the team or the company delivers the product can make a real difference. After all, an application or software is developed to answer a particular problem or address a specific challenge promptly. It is important to use the product when the need is still there. The rush to deliver faster often results in poorly designed software. The software product is not well-thought, and development is mainly focused on developing functionalities. There can be a prior agreement at the beginning of the project between the product owners and the development team to launch the first features faster and allocate time to correct them later on to reduce time to market.

Poor scheduling: Underestimation during the software development estimation process often causes tech debt. The development team focuses on the respect of time estimates and accumulates lots of bad practices that they ultimately have to pay for. Poor scheduling can cause tech debt by forcing developers to take shortcuts, skip important steps, or rush through tasks to meet unrealistic deadlines. These actions can result in low-quality code that requires additional maintenance and refactoring in the future, leading to increased technical debt.

Bad development practices: It is crucial that the development team has a set of practices and conventions so that there is little or no significant difference in design and implementation from feature to feature. A lack of good development practices and conventions will lead developers to implement their design, rebuild over and over the same logic and format their codes the way they want rather than the way it is commonly accepted in the particular software project.

Outdated technology: As technology evolves, software standard becomes higher every day. With each improvement, new tech debt can arise. The choice of outdated technology makes it difficult to maintain and update software systems and limits the ability to adopt new technologies and development practices. This can result in increased costs and effort required to maintain the system, as well as reduced competitiveness and innovation in the long run.

Now that we have more understanding of what is tech debt and how we get it in our projects. Let’s see ways of measuring technical debt.


We have previously explored what is technical debt. This is important for measuring technical debt accurately, as the estimation depends on its nature. The most common types of code debt are:

Source code formatting: This is very common, but fortunately, this is the easiest to fix. Using the right tool and template during and even better before starting the development process can reduce this kind of tech debt dramatically.

Low-test coverage: Test coverage is an essential measure of code quality, especially when we use Agile methodology to support the development process. Tests ensure that each part of the code behaves in the intended way. A very low level of test coverage reduces the certainty of the accuracy of the software’s behavior and makes it difficult to solve problems when they occur.

Lack of modularity: That generally results from poor code design. Some codes sometimes serve different business logic. The more code developers write the more lack of modularity can be a bottleneck. It is harder to manage the software with logic all over the codes and parts of codes handling several logics.

Code complexity: Complexity can be measured in several different ways. It measures the dependence and path length to perform an operation. A long path leads to complex code.

Lack of documentation: Documentation is part of software development best practices. The software is often driven to evolve. It is important that the written code is always understood at all times by everyone who may be involved in the development process.

Now that we have identified the types of code debt so let’s see how to estimate them.


Now that we have reviewed the types of code debt, it is crucial to find the right approach how to measure technical debt. In no way should it be calculated manually since doing so will require going into the code and detecting all issues inside, and then estimating all possible issues one by one. It is not only time-consuming to proceed that way, but it is almost impossible to estimate evolving codes. At the point when measuring technical debt is done, the codes already have a different state.

One approach is to perform a static analysis of code using tools that support the analysis. The following is a list of the most popular tools used:

There are two ways to measure technical debt. The first one is to get a ratio according to code volume; the second one is to use directly the estimates given by the tools (like SonarQube), along with the list of tech debts and their references to the codes. SonarQube gives an estimate of the days or hours needed to fix these debts. For the ratio approach, we can use the initial estimates or, even better, the overall time needed to develop the software so far and extrapolate the value according to the technical debt ratio. The time needed for the development is very accurate, so measuring technical debt from the ratio can give an accurate estimate of the work needed to fix the issues.

Measuring technical debt gives us an approximate time needed to fix it. Fixing tech debts costs money; it would take additional man-days from the development team to fix them. The more tech debts there are to be fixed, the more time the development team would need to fix them. Leaving them inside code is not an option; if left uncorrected, tech debts will lead to more tech debts that would make future changes more and more difficult. Even though attempting to reduce technical debt can be costly, not addressing them earlier will cost more money in the future.


Measuring technical debt is crucial in software development for several reasons:

  • Identifying tech debt 

It enables development teams to identify areas of the software that may have accrued technical debt. It helps to detect and prioritize technical debt that needs to be addressed, allowing teams to allocate resources efficiently.

  • Prioritizing codel debt 

That helps in prioritizing technical debt by understanding the areas that pose the greatest risk to the software’s stability, security, and maintainability.

  • Estimating development efforts 

Measuring technical debt also helps in estimating the development efforts required to address code debt. It provides a better understanding of the time, resources, and costs involved in resolving technical debt.

  • Improving software quality 

It also allows development teams to track debt over time and improve the software’s overall quality by identifying areas of improvement and reducing the risk of future technical debt.

  • Enhancing business value

Measuring technical debt helps enhance business value by improving the software’s overall quality, reducing maintenance costs, and improving customer satisfaction.

However, measuring tech debt can be challenging. Some common challenges include a need for clear metrics, difficulty quantifying codel debt, and differing perceptions among development teams, product owners, and stakeholders.

Despite these challenges, measuring technical debt is essential in software development. It helps prioritize code debt and allocate resources more effectively, reducing development time and costs, improving software quality, and enhancing business value.


Being Agile is the best way of managing technical debt and reducing them when they appear. The sooner we address the issue, the less interest is going to pay over time. The software development team can use the following approach.

The quickest to solve: Fixing debts that take little time to fix is an excellent way to eliminate tech debt gradually. Debts like code formatting can be solved in a little time by making up a template and applying these templates to all the codes that have been developed so far, then integrating these templates into the tools used by the developers.

Priority: It is also important to address issues by priority. All issues that can lead to more significant issues should be addressed quickly and should be prioritized to avoid accumulation.

Technology update: When outdated technology leads to tech debts, it is important to update the software to the newest versions of the frameworks, application servers, databases, etc. It is even important to include every stable evolution of a framework used, for instance, always to have the latest update and to bring small changes without breaking the software.

Refactoring: Reviewing the software architecture and refactoring codes can often be useful when we don’t want to end up with duplicate code or codes that lack modularity.

These are useful approaches on how to reduce technical debt, but how to handle code debt in agile? Since resolving this issue is a continuous goal the development team should aim at, they should be entered in the product backlog as a user story and should be prioritized like any user story. The prioritization should take into account the impact of not managing technical debt identified at the beginning of a new iteration. When deciding which stories to include in the next development iteration, we should analyze whether postponing tech debt correction for the next iteration is more or less advantageous in the long term. As a rule of thumb, we should address every critical issue as soon as it is identified.


Managing technical debt is critical for software development teams to ensure the software remains stable, secure, and maintainable. Here are some best practices for managing technical debt:

  • The first step for managing technical debt is to acknowledge its existence. Development teams should regularly review the codebase to identify and prioritize it for resolution.
  • Prioritizing tech debt is essential to manage it effectively. The team should prioritize technical debt based on its severity, impact on the software, and potential to cause future problems.
  • Once the technical debt has been prioritized, development teams should estimate the effort and impact of addressing it. This will help to determine the resources required to resolve the code debt and the impact of addressing it on the software.
  • Establishing clear coding standards and guidelines can help prevent technical debt from accruing in the first place. Teams should establish coding standards and guidelines addressing code quality, documentation, testing, and security.
  • Automated code quality and security checks can help to identify technical debt early in the development cycle. The development team should use tools such as static code analyzers, code linters, and vulnerability scanners to automate code quality and security checks.
  • Refactoring and re-engineering are essential for managing technical debt. Developers should refactor and re-engineer code as required to eliminate it and ensure that the software remains maintainable, scalable, and secure.
  • Product owners and stakeholders should be involved in the technical debt management process. They should be aware of tech debt and its impact on the software’s stability, security, and maintainability.

As a result, managing technical debt is critical for software development teams to ensure that the software remains stable, secure, and maintainable. By following these best practices, development teams can effectively manage technical debt and ensure the long-term success of their software.

What is your favorite approach to tech debt management, and why?

Leave your thoughts and questions in the comments section. We’d be glad to have the discussion. Existek is an offshore software development company with extensive experience in consulting and project rescue.

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Having tech debts at some point in the software development process is quite usual. However, managing technical debt is important to avoid its accumulation over time. Sometimes, it may be required to accept a certain amount of tech debts, but ultimately there should be kept at an acceptable level at which they don’t harm the performance and the overall experience of the software product users.

Contrary to the estimation of development time, the technical debt measurement is based on existing codes that often evolve. It is then necessary to have a good approach how to calculate technical debt included in the software developed. Due to the ever-shifting nature of the code and the volume of codes to be evaluated, it is not possible to perform a manual estimation. It is then necessary to work with the right tools that allow an automatic computation of estimates.

Although addressing tech debts can cost money, leaving it in the software will cost more money in the future.

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Frequently asked questions

What is technical debt?

Tech debt refers to maintaining and improving software code that was developed quickly or without proper attention to quality, which leads to increased complexity and difficulty in making changes in the future. Essentially, it's the accumulated consequences of taking shortcuts or making compromises in the development process.

What are the types of technical debt?

The common types of tech debt include:

  • Source code formatting
  • Low-test coverage
  • Lack of modularity
  • Code complexity
  • Lack of documentation

How to measure technical debt?

There are several metrics and tools available for measuring technical debt. These metrics help development teams to understand the level and impact of technical debt on the software. Here are some common metrics:

  • The technical debt ratio
  • Code coverage
  • Code complexity
  • Code duplication

How to reduce technical debt?

The team has to cover the following aspects to adopt an efficient approach:

  • Quick solutions
  • Priority
  • Technology update
  • Refactoring
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