Get Ahead of Technical Debt: Learn How to Identify, Measure, and Prevent it

Technical debt is one of the software industry’s most well-known analogies for debt. It gives a chance to conceptualize the software’s quality measurably and objectively.
Certainly, technical debt is less subjective than a concept like “code smells,”—which attracts our logical minds.

The tech debt concept is frequently criticized for not being as quantifiably accurate as it is claimed to be, which is true. So in this article, We’ll demonstrate how technical debt may be measured in real-world scenarios. Until we get there, though, it’s critical to convince you that technical debt measures are worthwhile.

So, without further ado, let’s get rolling.

What Is Technical Debt?

Types of Technical Debt

As we’ve seen previously, technical debt is a typical outcome of application development and product development services, and part of it is justified. And certain kinds of technical debt are more damaging than others. Following are the different types of Tech debts:

1. Planned Technical Debt

When a business decides to incur some technical debt after carefully considering the repercussions, it incurs this kind of debt (risks and costs). If an enterprise anticipates making trade-offs in its anticipated technical debt, it must be as specific as possible.

2. Unintentional Technical Debt

This unintentional technical debt develops as a result of

• Poor habits
• Unfamiliarity with modern coding methods,
• Rollout problems.

Unintentional technical debt is a design strategy that leads to many errors. This kind occasionally results directly from a lack of coordination between the development and operational departments or inadequate communication inside the organization.

3. Unavoidable Technical Debt

Unavoidable debt develops because businesses evolve and technology advances over time, bringing better alternatives to the fore. It generally occurs when mid-project plan adjustments are sought, which have an immediate expense, like adding a brand-new functionality to an existing structure to accommodate mobile delivery better.

4. Software Entropy

Software entropy, also called bit-rot, develops gradually as the application’s quality deteriorates, resulting in usability issues, errors, or the need for upgrades. Entropy happens when many developers—many of whom might not comprehend the functional requirements and layout – make little adjustments that complicate the code, violate NFR specifications, or gradually damage it.

Why Should You Measure Technical Debt?

Now that you have a better understanding, you most likely see it as a problem that needs to be fixed.

Great! What approach would you take there?

You can use many techniques to reduce technical debt, including test automation, coding standards, and refactoring. Nevertheless, you need to assess the reasons for measuring technical debt before you begin addressing it.

A Few Grounds for Measuring Technical Debt are:

1. It enables you to evaluate the project’s financial viability.

Some of the code may be already in poor form, but since it doesn’t affect many modifications and isn’t a crucial region, it makes little sense to fix it.

2. It may enable you to identify a more straightforward answer.

It’s possible that a subsystem responsible for your poor “scores” would shortly be shut down. Therefore, it makes little sense to fix it as you’ll quickly discard it.

3. You can use it to find low-hanging fruit.

You might find areas of the codebase that are relatively simple to improve, allowing you to start winning immediately.

Measuring Technical Debt: Identify High-Risk Areas

1. Maintain a Complexity Log

Monitoring complexity needs to be one of the immediate actions when attempting to identify high-risk locations. Although there are many different types of code complexity, cyclomatic complexity (Cyclomatic complexity, to put it simply, is an assessment of the number of logical branches present within a function for the procedure.) is the most straightforward statistic you can monitor.

The minimal test cases required to ensure complete branch covering of a function are inversely correlated with cyclomatic complexity. Lowering cyclomatic complexity helps lessen a particular code’s total cognitive burden since code is easier to comprehend and manage.

2. Track Rework Ratio

In the parts of the codebase that experts alter the most frequently, errors are much more likely to be introduced. Additionally, it is a red flag when a code section undergoes several modifications. That could be a result of a lack of information or experience, bad code review procedures, or even inadequate requirements communication to the programmer.

You should monitor this parameter, also known as the rework ratio, & endeavor to maintain it as low as possible. A significant rework ratio is a red flag that something isn’t quite correct and can also be the root of future issues. There is a greater chance of defects entering the production environment when there is a large percentage of rework in the code.

3. Quantify Your Testing Activities

Another expense that needs to be quantified is software testing. A codebase’s lack of complete automation testing, particularly unit tests, is a better indication of technical debt. Without tests, programmers are hesitant to modify code or make additional modifications that may improve the codebase’s overall health out of concern that they could damage something. When that occurs, the quality of the code degrades quickly.

Monitoring code coverage is one of the methods used most frequently to evaluate test coverage. Among the several methods of code coverage.

Measure Risk and Add Relevance to the Mix

You may assess the risk associated with a specific area of the codebase using the metrics mentioned above, particularly the rework ratio. One example is a code with a higher rework ratio, low code coverage, and high code complexity. A codebase’s components don’t vary just in terms of risk, though. Their importance or criticality differs as well.

Furthermore, think about exporting noncritical code to other modules if the codebase is excessive. By doing this, you can increase the codebase’s signal-to-noise ratio while analyzing technical debt. You also encourage the reusing of code throughout your enterprise.

What Actions Should Be Taken To Address Technical Debt? A Focus On Prevention

1. Test Automation

Manual testing is largely ineffective. Therefore, don’t waste your time doing it. Test automation has become one of the best strategies for lowering or eradicating technical debt. Automated testing decreases code bugs by using automatic debugging loops and other procedures to check the code for issues whenever a module is upgraded.

2. Project Organization

Organizing your project more effectively is one of the most effective strategies to reduce technical debt. Teams may check the status of their enterprise development projects and stay on schedule using project management software like Hive Trello.

3. Create Best Practices for Your Code

Enterprises must create a document outlining coding guidelines and best practices for programmers to adhere to when their developers follow coding guidelines and standards.

4. Opt for Outsourcing

Suppose you’re like the majority of executive leaders. In that case, you want to boost productivity (62% of respondents), decrease errors (53%), optimize current procedures (52%), obtain access to fresh new concepts and innovations (51%), and reduce expenses (44%). All of the categories mentioned above can benefit from outsourcing. Not only that but by outsourcing, you can also lower technical debt.

[Also Read: Managing Technical Debt: A Roadmap for Large Software Projects]

Wrapping Up

It’s not necessary for the technical debt and overall code quality to be an ill-defined, arbitrary concept. Quite the contrary, you can and must evaluate it. That is essential if you want to stand a chance of combating and eliminating code rot.

As I previously stated, technical debt slows down your team’s future progress. Additionally, it ends up making adding new functionalities more challenging and can demoralize engineers. It can also lead to the introduction of more bugs.

Although technical debt is metaphorical, the revenue you lose as a consequence is not. Keep your programmers happier, reduce technical debt, and avoid squandering money.