Test-driven development (TDD) is a development process that lets you design your system with tests in mind. It’s not a substitute for software design or testing but a programming practice that involves translating requirements to test cases and executing those tests before implementing the code. TDD ensures that you understand what you are trying to build, how the pieces will fit together, and what the side effects could be. It’s a way to think through the requirements and the best design possible to implement the functionality.
Traditional software development is a linear approach where the project proceeds in a sequential manner starting from requirements gathering then analysis, design, coding, testing and deployment. Here you write your functional code first and then write the testing code, if you write it at all. This concept is often referred to as the Waterfall Model, and if you discover a critical flaw at any stage, you may not have a choice but to start all over again.
TDD completely turns this traditional development approach around. TDD methodology was developed by Kent Beck, creator of the Agile development methodology extreme programming (XP). The intention behind XP was to deliver higher quality software and responsiveness to changing business needs. TDD and unit testing evolved from extreme programming. TDD provides constant feedback and ensures that everything works as intended. Just like Agile, TDD has small iterations. The developers write test cases to cover new functionality, which guarantees immediate feedback—crucial in Agile methodology—before writing the actual code necessary to make those tests pass and then refactoring the code to make it more maintainable. It is an iterative approach where coding, writing unit tests, and refactoring are tightly interwoven.
TDD directly supports the Agile value of “Working software over comprehensive documentation.”
Red Phase: Developers create the unit tests and ensure that the test compiles. The test should fail at first as it lacks that feature.
Green Phase: After the test fails, developers make just enough code changes to make the test pass.
Refactor Phase: Once the test passes, code is refactored for any duplication in design and optimized to enhance performance without affecting external behavior of the program.
Repeat: Repeat all the above steps to accumulate unit tests for the software.
Code Quality: Promotes the development of high-quality code with significant reductions in defects.
Clear Scope: Helps define the exact required features by identifying any unwanted design or components.
Rapid Feedback: Provides a constant programming feedback loop.
Better Design: Helps ensure clean design by focusing on callable and testable operations.
High Acceptance: Tests can be easily generated from the acceptance criteria and usually meet the needs of the business.
Safety Net: Tests act as a safety net that guarantees any new changes won’t break the existing functionalities.
ROI: Cost to TDD is higher than not writing any tests at all but projects with no tests at all end up costing more in long term. No code coverage will result in more bugs and issues, which means more time spent on fixing defects than writing new features, which will result in the project being more expensive overall.
Scalable Software: Scalability comes with clean and maintainable code.
Code Documentation: Well written unit tests provide a working specification of the functional code and hence form an important part of the technical documentation.
Focus on one feature at a time and write short and readable tests.
Follow the right naming convention. Test classes should be named like implementation classes and test method names should be descriptive.
Write independent tests. Do not introduce dependencies between tests.
Tests should execute fast. Fast tests allow finding problems quicker and getting fast feedback.
Use mocks to reduce coupling. Unit tests should not depend on live objects as it can slow down the test execution speed.
Prefer ‘equals’ assertions to keep the tests simple.
It is important to understand where TDD can be helpful. For example, it won’t make too much sense when you do UI design changes or database changes.
Slower Speed: As the developers are more focused in writing unit test for features, it will result in slower development of code.
Learning Curve: Developers should know how to write unit tests. Lack of proper skillset can lead to redundant tests. Also, writing too large or coarse-grained tests is a common mistake.
Dependencies: Unit tests often have external dependencies, so they can be difficult to maintain.
Test Maintenance: Writing the tests is not enough. The tests should be maintained as the code evolves.
Code coverage is a metric in software testing that tells you how much of your code has been covered by tests. If code coverage is 80%, it means 20% of the code is untested. Unit testing is the primary vehicle for driving code coverage. This also exposes the dead code—untested or under-tested parts of the application—providing an extremely powerful insight into risks. While high code coverage does not guarantee appropriate use of TDD, coverage below 80% is likely to indicate a lack in the quality of code.
TDD is not a cure-all and doesn’t replace testing, but it’s an evolutionary approach to development that focuses on writing clean code that works. To successfully implement TDD, you must learn to take small steps when writing code and be persistent if you want the numerous benefits in terms of cost-efficiency in the long run and delivering true value to business.