7 Essential Metrics to Measure Tech Debt
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7 Essential Metrics to Measure Tech Debt

January 24th, 2023
Developer productivity metrics
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As an executive in a tech organization, it is crucial to keep track of potential roadblocks that might impact the business’s overall success. This includes technical debt, also known as code debt or tech debt. This happens in the code-writing process, when quick fixes intended to move projects forward start to accumulate. 

Projects with strict time constraints, lack of resources, lack of clear requirements, or pressure to deliver the product quickly can lead to engineers taking shortcuts in the code writing process.  

Additionally, some engineers may take shortcuts in order to quickly test an idea or prototype a feature, with the understanding that the code will eventually need to be refactored or rewritten in a more robust or maintainable way. In the short term, these types of solutions are sometimes inevitable but they only become an issue when left unreviewed for long periods of time. 
Keeping tech debt under control is crucial to your organization’s health and success in the long run because it can negatively impact current workflow, product functionality, and even market competitiveness. A platform such as Waydev can give you crucial metrics that help you get a better grasp of where tech depth accrues and how to prevent that. For example, our  Work log report gives you a clear picture of the engineering teams’ work habits, where they are most productive, and where issues may arise.

Understanding Tech Debt: Definition and Key Points

The term ”technical debt” was first used by Ward Cunningham who is one of the software developers that co-wrote the Agile Manifesto. He compared technical debt to financial debt, stating that when you want something fast, you borrow a larger sum to get it quickly instead of saving money for purchasing it later. But you also have to assume paying interest until you can pay back the whole sum, so a quick fix will always have drawbacks to consider. 

Much like financial debt, tech debt is a fast and convenient solution but you need to factor in what it will cost you to revise and fix it later in the process. When doing so, consider if the costs of adding a new feature to comply with customer need or getting the software faster to the market outweigh the costs of the interest. This means knowing that the shortcuts your teams have taken will need refactoring later, as they could cause problems or interfere with subsequent work. Is the faster result worth that cost? 

Think of tech debt as a way of getting ahead – it means finding quick fixes to get a particular section of work done and thus avoiding stalling a sprint, for example. The main causes for tech debt is prioritizing speed over quality, insufficient information over the users’ needs, or having to address dated architecture that no longer scales. 

A certain amount of tech debt is inevitable because time constraints won’t allow your teams to spend a large amount of time on writing only clean code. The pressure of fast product release is even greater on start-ups that can’t afford to support operations for long periods of time without making money from selling their products. Getting new features out on the market quickly also holds a lot of value because it means faster user feedback, and this can tell you a lot about their real needs. The key is to find a balance by not letting too much tech debt accumulate and paying your ”interest” in a timely manner, by regularly having developers assess and revise the items in the backlog. 

The Main Types of Tech Debt

Some suggest that solutions resulting in tech debt are generally based on informed decisions considering project constraints, such as delivery deadlines. This explanation entails that when engineers make a mistake resulting in bad written code, without understanding that it’s just a temporary solution that needs to be addressed later, this cannot be considered tech debt, but rather just poor designing skills. 

Martin Fowler defined the tech debt types in a paper by placing them in a Technical Debt Quadrant. His theory contradicts the hypothesis that tech debt is only intentional and fully assumed. This way of looking at tech debt speaks to the intention behind the proposed solution – was it an intentional decision due to project constraints or was it unintentional? As the name suggests, there are 4 main types of tech debt within this classification:

A different classification arose in 2014 when a new paper called ”Towards an Ontology of Terms on Technical Debt” defined the tech debt types considering their nature or area where they come up. Here are the types enounced here: 

a team of people around a table

Tech Debt Measuring: The Importance of Tracking and Managing Your Technical Shortcuts

As we’ve seen, tech debt can stem from various sources. While it may seem like a necessary evil in the short term, as the codebase grows, these quick fixes will start to accrue and create problems in product functionality or interfere with developers’ current work. Thus, failing to track and manage tech debt can lead to a spiral of increasing costs and consequences. 

Measuring tech debt is essential for understanding its scope and impact, as well as for making informed decisions about how to prioritize and address it. 

Some of the most common effects of tech debt are:

How to Deal With Tech Debt: Best Practices for preventing tech debt from accumulating in the first place

Even though writing less-than-perfect code is unavoidable, there are many ways to manage tech debt so that it doesn’t accumulate and take too much of a toll on your teams’ productivity and ultimately, the success of your projects and entire tech organization. Here are some of the best practices to keep tech debt under control.

people in a meeting
  1. Put tech debt in scrum planning 

Overlooking items that are in the backlog is easy and the more time that passes, the more these items are likely to accumulate and cause problems. Software development teams often prioritize creating new features over fixing bugs, so the tech debt will grow along with the codebase. A very good practice is to include revising tech debt in current workflow planning, so they will appear as tasks that need addressing. This way developers can’t overlook them and better solutions will replace the flawed written code. 

  1. Careful planning 

When dividing large pieces of work into smaller, more manageable tasks for developers’ teams, think carefully about time management. Setting very short deadlines or including a large amount of work within a sprint will likely cause developers to resort to quick but not clean written code, resulting in tech debt. Try to set more realistic goals that will allow teams to search for better quality solutions in the first place that won’t need revising later. 

  1. Automated testing

Automated testing will validate if the software functions properly and it’s faster and less costly than manual testing. It also includes automated debugging cycles that can result in identifying and reducing tech debt. 

  1. Code and architecture refactoring

In software development, refactoring means making small internal changes to improve quality without altering the product’s external behavior. Applying this practice is ideal when dealing with tech debt because it allows rewriting more reliable code without downtime. Refactoring can improve the design, functionality, and structure of software products. 

  1. Use specific metrics to track tech debt

Using engineering management platforms to track the progress of your projects and how the development processes work is a great way to stay on top of tech debt. This way you can have a clear view of where it most often occurs and identify possible causes, such as poor task planning. More than that, keeping a close eye on tech debt can also help you as an executive make a plan on dealing with it before it accumulates, and pay off your debt before the interest becomes more than the result is worth. Our Executive Reports helping you keep tech debt under control, by providing you with crucial metrics, such as code complexity or lines of code. 

Unlock the Power of Measurement: Discover the 7 Key Metrics for Assessing and Managing Tech Debt

As an executive in a tech organization, it is essential to have a comprehensive view of your engineering teams’ efficiency and where there’s room for improvement in allocating resources and time management. By staying informed on your teams’ processes in developing software you can have a better understanding of where tech debt may accrue and start planning how to best avoid that and solve existing backlogged items in a timely manner. This, in turn, may help you ensure that the system can scale as needed. 

Even though keeping track of all tech debt is nearly impossible, a number of software development metrics can help you grasp where it’s emerging and the impact it has on your tech organization’s long-term success. Waydev can help you keep track of your teams’ codebase, and overall progress in resolving current tasks and addressing tech debt, using crucial metrics that offer real-time data and powerful insight into the development processes. 

lines of code
  1. Cycle Time

Cycle time is a vast metric that tells you the time past from the first commit to product release. It is a very important metric that also tells you how long it takes for engineers to fix bugs – long hours indicate there is a lot of tech debt in the codebase. 

By measuring cycle time and comparing it to industry standards or previous performance, it can provide a good indicator of how much tech debt is affecting the development process and how much it is impacting the delivery speed. Additionally, tracking the cycle time over time can help to identify trends and patterns that may indicate an increasing level of tech debt.

  1. Code Complexity

Code complexity shows you the overall quality of code written by tracking metrics such as lines of code, class coupling, or depth of inheritance. As the codebase grows, so does the complexity of the code written and this is bound to result in more tech debt, as the product development progresses. So it’s important to keep track of the overall code quality and the implied tech debt that comes with the territory. 

With Waydev you can gain insights into the codebase, including metrics such as code complexity, duplicated code, and code review times. By analyzing these metrics, Waydev can help you identify areas of the codebase that are most in need of refactoring or improvement, which can help you determine the level of tech debt

  1. Defect Density

Defect density is a measurement that can tell you the report between the number of flaws found in software products and the software size over a development cycle. The resulting number is a good indicator of code quality and the parts of the codebase that are more likely to fail over time. These will turn into tech debt, so this metric is an important component of determining potential sources for unreliable code. 

  1. Code Ownership

It’s important to keep pieces of work with clear ownership and with contributions from fewer developers. The more developers that contribute or revise pieces of work, the more likely it is for this to result in unreliable code. This happens because of incomplete information about the specifications or requirements of a particular part of the codebase. The practice of diluted ownership results in more tech debt that accrues over time. Measuring code ownership and assessing whether it’s kept in small groups will give you an indication of engineering practices’ health. 

  1. Code Churn (Rework)

Code churn is when code has been deleted or rewritten in a short period of time. A certain amount of churn is usually understandable with new features, but if the ratio is higher than 9-14%, this may be an indication that the initial code was a quick fix and not a reliable solution. Churn spikes may be an indication of engineers being stuck on a task so it is important to understand when that happens. 

  1. New and Closed Bugs

Tracking how many bugs your team opens versus how many it closes is a good measure of their development process. Closing bugs is great, but if your teams are creating many new bugs as they close others, this is a sign that they are using quick fixes instead of finding long-term solutions.

  1. Legacy refactor

Legacy refactoring speaks to how much time an engineer spends rewriting existing code versus how much they are spending working on new features. Software development is fast-paced and needs engineers’ and developers’ output to keep up with client’s requirements. So while there is a need for addressing tech debt, new work cannot be neglected either. Measuring the ratio between these two indicators will help you get a better understanding of whether there is a balance between them. 

Master Tech Debt and Keep Your Codebase In Check

As a high-level executive in a tech organization, it’s crucial to understand the importance of measurement in managing tech debt. While a short-term amount of tech debt can be manageable as long as it’s acknowledged, it’s essential to have a clear view of where it’s causing problems such as decreased productivity, reduced competitiveness, or increased costs.

Intuition on the sources of tech debt isn’t enough for informed decisions, but rather you need comprehensive metrics that will show you the development process in-depth. This will help you understand why tech depth appears and whether it’s a higher ratio than the norm. By keeping track of tech depth you are able to decrease existing debt and avoid unnecessary quick fixes in the future. 

With comprehensive dashboards that log workflow, Waydev can provide the big picture that you need for better resource planning and identifying potential problem areas. Don’t wait for the problem to escalate, take action now and implement a strategy for measuring and managing tech debt to ensure the long-term success of your organization.

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