Test-Driven Development (TDD) - What it is and How to Implement it

In TDD, developers write tests before the actual code.

The basic idea is to set out how your code should behave by writing a test that initially fails. Then, you write just enough code to make that test pass. Finally, you refactor (or “clean up”) the code without breaking the test.

This red-green-refactor cycle is at the core of the test-driven development framework. By writing tests up front, you create rules your code must satisfy. It’s like having a checklist before building something, ensuring you know exactly what you aim for.

The test-driven development process follows a straightforward, repeatable cycle.

Write a failing test

The first step is to write a new test for the functionality you want to add to your codebase. This test should initially fail because you haven’t written the code to make it pass yet.

Writing the test first defines the specification or requirement for what you’re about to build.

Run tests and see it fail

After writing the new failing test, run your existing test suite (including the new failing test) to verify that the new test fails.

This step helps validate that your new test is written correctly and catches the absence of the functionality you’re about to implement.

Write just enough code to make the test pass

Next, it’s time to write the minimal production code required to make the failing test pass.

TDD emphasizes writing simple, straightforward code that meets the test’s requirements without worrying about optimization or edge cases at this stage.

Run tests and see them pass

You can rerun your tests with the new code, including the one you just coded against.

Verify all tests are now passing, giving you confidence that the new functionality works as expected.

Refactor

Once you have a passing test, you may refactor the code to improve its design, readability, or performance.

It’s essential to refactor without breaking existing tests. This helps keep your codebase clean and maintainable.

To better understand the process, let’s illustrate TDD with a real-life example: building a shopping cart feature on an ecommerce app.

You start by writing a failing test for the most basic shopping cart requirement: the ability to add an item to the cart.

Here’s what that test might look like in Python:

Since you haven’t written the ShoppingCart class yet, this test will fail when you run it.

We now write just enough code to make the test pass:

Rerunning the test suite, you’ll see the initial test now passes.

The code works as expected, so you might refactor it to improve its design or readability. For instance, you could create a separate Item class to represent each item in the cart.

With the basic “add item” functionality in place, you continue the TDD cycle by writing more tests for additional requirements, like removing items from the cart, calculating the total cost, applying discounts, and so on. Each new test drives the implementation of the corresponding product feature.

Following a TDD process enables you to build your ecommerce app one small piece at a time, guided by automated tests that define the expected behavior. This ensures the product is thoroughly tested, works properly, and is less prone to breaking as new features are added or existing ones are modified.

Understanding the pitfalls and advantages of test-driven development is crucial to a smooth transition.

In most cases, the benefits far outweigh the costs for teams fully embracing the practice. However, weighing the trade-offs and finding the right balance for your team and project needs is essential.

Here are some of the main pros and cons of TDD.

Pros

• Better code quality: Writing tests first helps define your requirements upfront, resulting in more robust, bug-free code. One study found that 92% of developers believed TDD yielded higher-quality code.

• Documentation: Tests act as live documentation, making it easier for new developers to understand the codebase.

• Modular design: TDD promotes a modular design approach, improving code maintainability and extensibility.

• Refactoring safety net: A comprehensive test suite enables confident code refactoring without breaking existing functionality.

Cons

• Learning curve: Test-driven development in agile teams requires changing your working methods and attitudes, which can be challenging for new adopters and cause a delay in implementing it.
• Upfront time investment: Writing tests before production code can initially feel counterintuitive and time-consuming, leading to slower implementation. A survey discovered that, although 41% of the respondents said their organizations have fully adopted TDD, only 8% said they write tests first 80% of the time.

• Testing challenges: Some types of code (e.g., user interfaces or third-party integrations) can be trickier to test effectively.

• Maintenance overhead: As the codebase grows, maintaining and updating tests can demand more resources.

In traditional software development methodologies, developers often treat testing as a separate phase after writing the code.

This approach is sometimes called the “Code First, Test Later” model. The main steps typically look like this:

1. Gather requirements
2. Write code
3. Write tests (if time permits)
4. Run tests
5. Fix bugs
6. Release

With TDD, testing is not an afterthought—it shapes the entire development process from the start.

Unlike the traditional model, where tests validate the code after it’s written, TDD uses tests to define the requirements and the code upfront.

Most organizations now combine TDD with other testing practices, such as integration and end-to-end testing, for a well-rounded strategy.

While test-driven development (TDD) and behavior-driven development (BDD) are closely related concepts, there are some distinctions between the two.

As we’ve highlighted, TDD is a developer-centric practice focused on writing unit tests before writing code. The tests define how the software's units (such as methods or functions) should behave.

BDD, on the other hand, is a team-centric practice that emphasizes collaboration between developers, testers, and business representatives. Instead of unit tests, BDD uses higher-level specifications called feature files or scenarios written in a format everyone on the team can understand.

BDD:

• Operates on the feature or behavior level
• Uses specifications written in a readable, domain-specific language (DSL), such as Gherkin
• Involves the whole team
• Focuses on user stories and desired behavior

TDD:

• Operates at the unit or method level
• Uses tests written in code using testing frameworks (e.g., JUnit for Java, RSpec for Ruby, etc.)
• Is primarily used by developers
• Focuses on code implementation details

Whereas TDD helps ensure correct code implementation, BDD bridges the gap between business requirements and technical implementation. It enhances communication and ensures the software behaves as intended from the user’s perspective.

Many teams practice BDD on top of TDD, using feature files to drive the development of unit tests. The two practices complement each other in building high-quality, well-tested software.

Adopting test-driven development can be tricky at first, particularly if your team is used to other ways of working. These best practices and tips can help your organization understand and benefit from TDD.

Write simple tests first

Start with the simplest possible test case for a new feature or behavior. Don’t try covering all cases in the initial test.

Writing simple tests helps you stay focused and avoid getting bogged down in complex scenarios early on.

Follow the red-green-refactor cycle

Resist the temptation to write more code than necessary to make a test pass. Stick to the TDD cycle of writing a failing test, making it pass with the most straightforward solutions, and then refactoring.

This discipline helps you build software incrementally and maintain a high-quality codebase.

Keep tests and production code separate

Maintain a clear separation between your test code and production code. Tests should stay in their directory or module so you can identify and manage them separately from the codebase they’re testing.

Use descriptive test names

Write test names that clearly describe the behavior or scenario under testing. Good test names act as documentation, making it easier to understand the purpose of each test and the functionality it covers.

Practice test organization and grouping

As your test suite grows, organize your tests into logical groups or suites based on the functionality or component they’re testing.

This practice improves test maintenance and enables you to selectively run specific tests or suites.

Embrace test automation

Automate your test suite to run tests with a single command or script. This enables you to run tests frequently (like after each code change or as part of a continuous integration pipeline), catching regressions early.

Mind the testing pyramid

Although TDD primarily focuses on unit tests, it’s important to strike a balance with other types of tests (such as integration and end-to-end) as your application grows.

Follow the testing pyramid principle, with a broad base of unit tests complemented by a smaller number of higher-level tests.

Involve the whole team

Encourage collaboration and shared ownership of tests among developers, testing, and other stakeholders. This helps ensure that tests accurately reflect the desired behavior from multiple perspectives and promotes a culture of quality and accountability.

Continuously refactor and improve

Treat your test suite as a living, evolving codebase. Continuously refactor and improve tests as you gain more knowledge and experience with the system under test.

Well-maintained tests are invaluable assets for long-term project health.

Having the right tools at your fingertips can massively improve your TDD practices.

Writing and running pre-code tests are crucial, but you’ll need solid insights and analytics to ensure your new approach pays off.

Here’s where Amplitude Experiment can help.

The platform’s features and data-backed experimentation approach support test-driven development in several ways:

• Behavioral and predictive data targeting: Target user segments based on their behavior or predicted behavior and define test cases and scenarios covering different user behavior.

• Flags for remote configuration: Remotely configure product experiences without deploying new code. Easily toggle features on and off for testing purposes during the TDD cycle.

• Integrated experiment design and analytics: Measure the impact of code changes on user behavior and define test cases based on data-driven insights using Amplitude’s integrated workflow—design experiments, link to existing analytics, and analyze the results.

• Scalable experimentation: Easily scale experimentation across your organization and support TDD adoption by enabling more teams to embrace an experimentation culture.