Development and testing go hand in hand: one can not be complete without the other. Traditionally, the emphasis has always been placed on developing. Developers code first, then test, fix any bugs they find, commit code, and the cycle repeats. Test-driven development (TDD) takes a slightly contrarian approach: test first, then write code later. These test results guide development activities.   
 

Although it may sound counterintuitive, TDD is actually a better approach to development and testing. In this article, we’ll explore in depth the TDD concept, its best practices, and how you can leverage it for a better coding – testing experience.

What Is Test Driven Development?

TDD, or Test-Driven Development, is the process of writing and executing automated tests before writing code. Insights from the tests help the developer improve the code. TDD reflects the spirit of continuous feedback, resulting in faster bug identification and debugging.

Test-Driven Development Cycle

TDD is a continuous, iterative process of improving code through tests. To do TDD, simply follow the mantra of Red - Green - Refactor cycle. Some may call it Fail - Pass - Refactor, but it’s all the same thing. 

The idea is to fail a test - make it pass - then rewrite the code. Let’s see how it’s done in detail here:

1. Write One Specific Test

You start by writing a test case for one specific feature. There is absolutely no code written for this feature yet. Essentially, we are writing the test for a feature that has not even been created.

Want To Write Tests Without Having To Code? It Starts From Here  

2. Execute the Test

It should be quite easy to see that this test will definitely fail. Counterintuitive as it may seem, this is where the ingenuity of TDD lies. There are four major rationales as to why we must fail the test:   
 

1. Running tests on early-stage code ensures the proper setup and function of your testing infrastructure. Any issues with the test environment can be addressed right from the start.   
    
2. A failed test is not inherently a terrible thing. Your code is not written yet, and the test fails, which is an encouraging sign that the test is dependable.   
    
3. This first test, along with future ones, is a checklist guiding your development activities. They become objectives to pursue (think: I code until the test is passed). It breaks down the seemingly overwhelming project into smaller chunks that can be tackled one by one. At the end of the day, TDD gives developers milestones to cross and project managers a more granular view over which features are being developed.   
    
4. TDD offers immediate feedback on code quality.   
    

Once you fail your test, you have reached the Red stage of the Red - Green - Refactor cycle.   
 

In other words, to do TDD is to have a different mindset. A failed test is a good test. There is no failure, only lessons to learn from.

3. Write the Minimum Amount of Code to Make It Pass

Now is the time to code. But the good thing is you don’t have to immediately flesh out a fully functioning and optimized application. Write just enough code to make it pass. After all, the goal of TDD is to use test results to guide development, not the other way around.   
 

In a way, this approach requires developers to shift their focus away from the bigger picture and how the application works as a whole to the little details satisfying the requirements of that particular test case they are working on. This promotes code minimalism.   
 

When we think of code minimalism, we think of:

• Simplicity
• Readability
• Focused functionality
• Modular design
• Testability
• Maintainability   
   

And that is exactly what TDD is capable of. It turns writing code into this kind of goal-based activity with short feedback loops while also guiding the coder to write code that is concise and straight to the point.   
 

TDD also automatically promotes loose coupling. When you write code for one test at a time, you don’t have to constantly worry as much about the impact a certain module has on another. They are designed to operate independently. As long as they work by themselves, it’s fine.   
 

Now that the code is ready, you can run the test until it passes. A passed test now indicates that the code meets the specified requirements as outlined in the test case.   
 

Once done, you have reached the Green stage of the Red - Green - Refactor cycle.

4. Continuously Run Tests and Refactor Code

We have arrived at the Refactor stage. To refactor is to restructure it to improve the code (of course without changing any external behavior). You have found the solution to the problem, but is it the best solution yet? Here you understand the underlying mechanism of your code so ideas for optimization should come more easily.   
 

The cycle repeats. Write another test. Run it and observe it fails. Write code for that test until it passes. Over time, you get more and more feedback from tests, continuously refactor the code, and improve its design, readability, and maintainability.

TDD Examples

Here’s a fun TDD example.   
 

We want to implement a function to calculate the factorial of a number. The factorial of a non-negative integer n, denoted as n!, is the product of all positive integers less than or equal to n.   
 

Here’s the test:   
 

import unittest
from factorial import calculate_factorial
 
class TestFactorialCalculator(unittest.TestCase):
    """Test the factorial calculator function"""
 
    def test_factorial_of_0(self):
        expected = 1
        result = calculate_factorial(0)
        self.assertEqual(expected, result)
    def test_factorial_of_positive_number(self):
        expected = 120
        result = calculate_factorial(5)
        self.assertEqual(expected, result)
 
    def test_factorial_of_negative_number(self):
        with self.assertRaises(ValueError):
            calculate_factorial(-5)
 
    def test_factorial_of_non_integer(self):
        with self.assertRaises(ValueError):
            calculate_factorial(5.5)
 
if __name__ == '__main__':
    unittest.main()

As you can see, our test has four scenarios:

1. test_factorial_of_0: Tests if the factorial of 0 is 1.
2. test_factorial_of_positive_number: Tests if the factorial of a positive number (5 in this case) is calculated correctly.
3. test_factorial_of_negative_number: Tests if the function raises a ValueError when trying to calculate the factorial of a negative number.
4. test_factorial_of_non_integer: Tests if the function raises a ValueError when trying to calculate the factorial of a non-integer (in this case, a float). 

You can run the test. Without any code written, it sure will fail. This is when we start to write code:   
 

# factorial.py
 
def calculate_factorial(n):
    if n < 0:
        raise ValueError("Factorial is not defined for negative numbers")
    elif not isinstance(n, int):
        raise ValueError("Factorial is only defined for integers")
    elif n == 0:
        return 1
    else:
        result = 1
        for i in range(1, n + 1):
            result *= i
        return result
 

Benefits of Test-Driven Development (TDD)

TDD is incredibly powerful once you get into the rhythm of it.   
 

For starters, it helps you stay focused on what truly matters. It is basically just a three-stage process that tells you to write code for one particular feature at a time. Absolutely no tool or special technique is needed, just plain old coding and testing as you have always done. However, you will soon find that it can automatically improve the design of your application. Each component is written for itself. Such independence makes it so much easier to maintain code during updates.   
 

Another cool benefit of TDD is that it makes you feel safe. You have tests confirming every step along your way. You make any changes you want, since you can always run the test and see if it passes. If it fails, you can always go back to a state before that, and start over.

TDD vs. Traditional Testing   
 

Scaling TDD via Agile Model-Driven Development (AMDD)

Here’s a table to compare TDD with AMDD (Agile Model-driven Development):   
 

How TDD Fits Into Agile Development?

The nature of Agile aligns well with TDD practices.   
 

The pillars of Agile are flexibility and collaboration, and TDD contributes to those pillars. TDD is iterative by nature, breaking down development into small cycles. Agile is the same. You can easily allocate TDD activities into Agile sprints.   
 

Agile teams also tend to be resilient against change, and TDD provides an additional safety net. When requirements change, developers can make adjustments confidently, knowing that they have a list of TDD tests ready to check the quality.

TDD Frameworks

Some of the popular TDD frameworks include:   
 

• JUnit (Java): Widely used for Java development. Supports annotations for test methods. Integrates with various IDEs and build tools.
• NUnit (.NET - C#, F#, VB.NET): Popular in the .NET ecosystem. Provides a framework for writing and running unit tests. Supports parameterized tests and setup/teardown methods.
• pytest (Python): Feature-rich testing framework for Python. Supports fixtures, parameterized testing, and plugins. Integrates with other testing tools and frameworks.
• RSpec (Ruby): Behavior-driven development (BDD) framework for Ruby. Focuses on readability and expressiveness. Provides a rich set of matchers for expectations.

TDD Best Practices

What to do:

1. Effective layout ensures completion of all required actions, improving readability and execution flow.
2. Consistent structure aids in building a self-documenting test case.
3. Commonly used structure includes Setup, Execution, Validation, and Cleanup.
4. Separate common setup and teardown logic into test support services.
5. Keep each test oracle focused on necessary validation results.
6. Design time-related tests to tolerate execution in non-real-time operating systems.
7. Allow a 5-10 percent margin for late execution to reduce false negatives.
8. Treat test code with the same respect as production code – it must work correctly, last long, and be readable and maintainable.
9. Teams should review tests and practices to share effective techniques and identify bad habits.   
    

What to avoid:

1. Avoid dependencies between test cases to prevent brittleness and complexity.
2. Be cautious of interdependent tests causing cascading false negatives.
3. Avoid testing precise execution, behavior, timing, or performance.
4. Avoid testing implementation details.
5. Be cautious of slow-running tests, as they can impact project efficiency.