Its 2025 And You Should Not Write Code Without Tests

In 2025, shipping code without tests should be a total no. In a landscape where deployments happen multiple times a day and services are expected to be available 24/7, undetected regressions can lead to downtime and erode user trust. Automated tests provide a safety net that ensures changes don’t introduce unexpected behavior, offering confidence and stability as applications evolve.

This blog draws upon insights from Clean Code by Robert C. Martin, Chapter 9: Unit Tests to explore why testing is an indispensable practice in professional software development.

Software development practices have evolved significantly over the decades. One of the most notable transformations has been in how developers approach testing. The journey from manual, throw-away tests to systematic, automated testing practices reflects a deeper understanding of what makes code maintainable and reliable.

Back in the mid-90s, unit tests were often just temporary code snippets used to verify if programs “worked” Developers would create simple driver programs for manual interaction testing. Today, the approach to testing has matured considerably, with systematic methodologies like Test-Driven Development (TDD) becoming standard practice in professional software development.

Why Tests Matter

Tests are not just a safety net, they are the foundation that enables code to remain flexible, maintainable, and reusable. Without tests, every code change becomes a potential source of undetected bugs. The fear of breaking existing functionality often leads to code stagnation, where developers become reluctant to make necessary improvements.

One of the most compelling reasons to write tests is that they enable all the desirable qualities of code, what are often called the “ilities”:

• Maintainability: Tests give developers confidence to modify code without fear of breaking existing functionality
• Flexibility: With a comprehensive test suite, code can be refactored and improved safely
• Reusability: Well-tested code is typically better designed and more modular, making it easier to reuse
• Reliability: Tests ensure code behaves consistently across changes and environments

Beyond these foundational benefits, a comprehensive test suite is becoming increasingly vital for effectively leveraging AI-powered development tools in 2025. Here’s how tests make working with AI assistants easier and safer:

• Executable Specifications for AI: Tests act as precise, machine-readable specifications of intended behavior. AI code generation tools (like GitHub Copilot or Qodo Gen) can use these tests as context to produce more accurate and relevant code suggestions, significantly reducing the need for manual correction.
• Guardrails Against AI Errors: When AI tools suggest refactoring, generate new functions, or even auto-complete snippets, your existing tests serve as an immediate validation layer. Running the test suite automatically after AI intervention provides confidence that the changes haven’t introduced regressions, acting as crucial guardrails.
• Grounding AI Suggestions: Providing relevant test cases alongside prompts helps ground AI models, reducing the likelihood of “hallucinations” or suggestions that don’t align with the project’s specific requirements or constraints.
• Facilitating AI-Driven Testing: AI tools are increasingly used for testing tasks themselves, such as generating new test cases, optimizing test execution, or identifying coverage gaps. A solid foundation of existing tests provides the necessary data and patterns for these AI testing tools to learn from and operate effectively.

The Cost of Not Testing

Let’s talk about what really happens when we skip writing tests. It starts small, maybe you’re under deadline pressure, or perhaps writing tests feels like extra work. But the problems snowball faster than you might expect.

Without tests, every code change becomes scary. Think about changing code that has no tests, even a tiny modification could break something somewhere else in the system, and you wouldn’t know until it hits production. That fear leads to developers taking shortcuts. Instead of properly fixing issues, they start adding quick patches just to get things working.

Over time, these shortcuts pile up. The codebase becomes more complex and fragile. Simple bug fixes that should take minutes stretch into hours or days because developers spend more time manually testing to make sure they haven’t broken anything else. The code starts to rot, becoming a tangled mess that everyone’s afraid to touch.

What’s worse, this creates a vicious cycle. The messier the code gets, the harder it becomes to add proper tests later. And without tests, it becomes even harder to clean up the mess. It’s like trying to renovate a house while blindfolded, you might fix one thing but break three others in the process.

In the end, what started as “saving time” by skipping tests ends up costing much more in time, money, and developer sanity. This is why professional developers insist on writing tests, not because they love writing tests, but because they’ve seen firsthand what happens when they don’t.

Test-Driven Development (TDD)

TDD is simpler than most people think. It follows three basic rules: write a failing test first, write just enough test code to fail, and then write just enough production code to pass that test. That’s it. This creates a tight cycle that usually takes about 30 seconds to complete.

Here’s what’s fascinating about TDD, when developers stick to this cycle, they end up writing dozens of tests every day. Do the math, those daily tests add up to hundreds in a month and thousands in a year. Soon enough, the test code becomes almost as large as the production code itself.

But this isn’t a bad thing. These tests become your safety net, your documentation, and your design tool all rolled into one. When you write tests first, you naturally create code that’s easier to test. The code becomes more modular, with cleaner interfaces and fewer dependencies. It’s like having a blueprint before building a house, you catch potential problems before they become expensive mistakes.

The real beauty of TDD shows up when you need to make changes. Instead of wondering “what might break if I change this?”, you can modify code confidently. If something breaks, your tests will tell you immediately. No more hours spent manually testing the entire application after every small change.

Yes, writing tests first might feel slower initially. But it’s like stopping to sharpen your axe before cutting down a tree, the small upfront investment saves much more time in the long run. You catch bugs earlier when they are cheaper to fix, you spend less time debugging, and your code stays clean and maintainable.

Remember though, just having a lot of tests isn’t enough. These tests need to be clean, purposeful, and well-maintained. They’re as much a part of your codebase as your production code, and they deserve the same level of care and attention.

Writing Clean Tests

What makes a test “clean”? It all comes down to one word: readability. A test should tell a story about the code. When someone reads your test, they should instantly understand what’s being tested and what’s expected to happen.

Clean tests follow a simple pattern: build, operate, check AKA arrange, act, assert. First, you set up your test data. Then you do something with that data. Finally, you verify that what happened matches what you expected. It’s like a cooking recipe, gather your ingredients, follow the steps, check if the dish turned out right.

Keep tests focused and simple. Each test should verify just one thing. If you find yourself writing “and” in a test name, you’re probably trying to test too much at once. A test named “createUserAndSendEmailAndUpdateDatabase” is doing too much, break it into three separate tests.

Remember, test code isn’t a place to show off clever programming tricks. The simpler and more obvious your test code is, the better. You might write a complex algorithm in your production code, but the test for that algorithm should be crystal clear to anyone reading it.

Conclusion

Automated tests not only catch bugs early but also unlock full automation of your development pipeline. With a comprehensive test suite, you can seamlessly integrate continuous integration and continuous delivery (CI/CD) workflows, enabling automatic builds, tests, and deployments on every code change. This accelerates feedback loops, reduces manual verification effort, and fosters rapid iteration without compromising stability. Moreover, well-maintained tests serve as living documentation, clarifying expected behavior and guiding future development. Embracing testing in 2025 lays a foundation for efficient development, higher code reliability, and ultimately, happier customers.