3 Main Types of Technical Debt and How to Manage Them

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managing tech debt

The team creates one buffer-task per release with e.g. 10% of the available time. Team members can record the time on that task for not yet scheduled refactorings. So it is used for yet unknown problems that might appear in the future. However, it also poses the risk that time is wasted on unimportant work.

Recently, I had to deal with an old codebase that was difficult to maintain and scale. In this article, I’ll share how my team and I decided to deal with maintenance and the best practices we implemented to reduce time spent on refactoring. You can prioritize based on vectors like confidence, time, impact to user, and more. Engineers, or others close to a piece of tech debt, will regularly reiterate that piece of tech debt as personally painful for them to deal with.

Processes To Reduce Tech Debt From Being Created

Article Tools to Track and Manage Technical Debt If you are looking for a tool to start managing technical debt this article will help you make the right decision. Article Stepsize vs Code Quality Tools Stepsize is a powerful tool that helps Engineering teams fight technical debt and improve their codebase health. Article How Arcane fixed 50% of their technical debt and improved productivity, quality, and morale Learn how the Arcane team achieved tech debt visibility and fixed half of their codebase issues with Stepsize.

managing tech debt

It was noted as part of project A, but due to work on Project B it is no longer an issue. Or it was important to update part of product A, but, for example, you’ve moved a lot of that underlying infrastructure to AWS so now it’s not actually a problem. The important thing is to make a note of the debt and track it; put it somewhere to make sure the conversation is active, but keep it clean. For a website, you may have specific objectives around load times or other metrics that can only be improved by addressing technical debt. For example, we recently underwent an upgrade related to how our application functions in a web browser. The previous framework was working fine but we realized new features we had in the pipeline we’re going to encounter some turbulence if things weren’t updated.


In each situation played out above, it’s important to consider the piece of tech debt critically, across each vector and the the low to high priority scale. Evaluating tech debt in this manner allows for the team to make the best strategic decision on how to move forward vs. other company initiatives also in the picture. If even more of the vectors – say impact to time, impact to user, and sequence were all smaller and to the left, then it’s likely okay to backlog this area of tech debt to a time that makes sense in the future. So far, we’ve gone through assumptions, classifications, and sizing in relation to tech debt. Once you understand those things you can make a strategic decision within the broader context of your product decisions. Some tech debt is good to have and every team needs to have tech debt.

Whether it’s because of code complexity, testing or any other issues, it adds time to the project that could have been fixed in an earlier stage. As a result, your developers will spend time addressing these problems rather than delivering other work with business value. When teams scramble to meet sprint deadlines, it usually results in lengthy methods, inefficient routines or low-quality code. If teams emphasize new features over resolving bugs, it also creates a technical debt that will need a resolution before it passes to the next development step. While deciding how you’ll manage your tech debt, you may want to consider what resources and time your organization will need to address it. This is all dependent on the types of debt you’re working with, how long paying down your technical debt will take you, and what technical debt you want to focus on.

You want to avoid a situation where a particular item falls through the cracks and remains undiscovered until something breaks. One strategy for building enthusiasm around debt-related activities is to dedicate time to illustrate what happens if you don’t address your technical debt. You also have to motivate staff to maintain quality work, or even reward it.

Fortunately, there are great methods to help you prioritise your product backlog. The 3 Best VS Code Extensions to Handle TODOsAs software engineers, we use TODOs and FIXMEs all the time. We’ve picked out the three best Visual Studio Code extensions to help you handle them.

managing tech debt

This is especially the case in Inflection and Scale stages of company growth, where developer efficiency debt should decrease as more engineers join the team. The developer efficiency debt decreasing What is Ruby can then give way to necessary increases in decision debt and maintenance debt. Despite this, most tech debt is classified under a single bucket of ‘bad’ or ‘burdensome’ because of the unknowns.

What are some examples of tech debt?

Ongoing development, long series of project enhancements over time renders old solutions sub-optimal. Technical debt always begins from the first day of development, even though not totally visible. You can’t completely take it out, but you can manage it and minimize it as much as possible.

It could be that they did not have the time to introduce DevOps, or maybe they did not have the budget. It could be that they did not think it was going to make enough of an impact. The larger the project is, the more technical debt the team takes on.

Strategies and approaches that worked well at one time may simply be outdated or inefficient. Newer methods can replace worn-out ones, and quick, inexpensive solutions can be swapped out for higher-quality replacements as resources allow. With agile, the focus away from schedules and towards high-quality, demonstrable software.

Though that’s a conscious debt, or an informed decision if you will, technical debt can also be created unknowingly or unintentionally. Leaving no annotations to the code, old and not addressed bugs, or no automated test, for example. Some amount of technical debt is inevitable, and it can be used as a valuable tool when the ultimate quality of the code isn’t critical or when time is. Technical debt can evoke consequences like losing customers because of poor experience, making a product more vulnerable and less performant, and increasing development costs. Technical debt is often caused by insufficient information about users’ needs, pressure to prioritize release over quality, and not paying enough attention to the code quality.

  • And, as time goes by, developers lose the context of the issues and become less inclined to address them.
  • And because you create technical debt the moment you ship code, strategizing how to address it can seem overwhelming.
  • At ProductPlan, we segment our NPS feedback to understand where users are satisfied—or dissatisfied—with the product web experience.
  • Teams and project managers are busy and often under the pedal to keep releasing updates and new products.
  • After all, a team’s culture regarding daily and regular functions can have a significant impact on technical debt on an ongoing basis.

They may struggle during QA around certain pieces of prehistoric code or altogether want to quit their job because the team is taking too long to fully adopt a new programming language. The employee might feel like it’s starting to become the end of the world for them, while the rest of the organization probably doesn’t feel the same pain . This is especially common for people early in their career, where their pain point seems like the most critical thing, due to a lack of broader strategic context. Overall, metrics will help teams keep track of technical debt more precisely and save time on its elimination. However, keep in mind that incorrect usage of metrics can result in a misleading determination of tasks and objectives.

How to measure technical debt (and reduce it)

Based on intent, tech debts can be of four types – reckless, prudent, deliberate, or inadvertent. OutSystems orchestrates the entire deployment process using a combination of automation, AI, and analytics to identify architecture errors, faulty logic, and broken dependencies—during development, in real-time. Reckless and inadvertent, when the team doesn’t have the experience and blindly implements the solution. The team doesn’t realize they are putting themselves into a gigantic mess.

How to Maintain a Healthy Codebase while Shipping Fast

If we have little refactorings, which only cost an hour or only a day, there’s no point in discussing it intensively, if they are really useful. “Pay as-you-go” is great if you know what you’re doing, if most of the team members have a good understanding of how to grow a system with a certain technology within a learning-notes the-phoenix-project md at master keyvanakbary learning-notes certain domain. You start with a simple solution, but you know you have to change your design while your system is growing. I would think a “real options”-based approach applied to managing technical debt w.r.t. cost-of-delay would make a lot more sense to use here (especially for the “pay-as-you-go” approach).

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