In the previous lesson, we explored the importance of code test coverage and how it ensures software quality and developer confidence. Now, we will explore a specific type of testing known as characterization tests. These tests are invaluable when working with an established codebase, as they help document the current behavior of a system without altering its functionality. By the end of this lesson, we'll understand how to use characterization tests to increase code coverage effectively.

Aren't these tests the same as unit tests but with a fancy name? In a sense yes, but we want to explore the nuance of looking at unit tests as characterization tests. Characterization tests are designed to capture the existing behavior of a system. They are particularly useful when dealing with an existing codebase that lacks documentation or tests. The primary goal of these tests is not to find bugs but to document what the code currently does.

Another important aspect of characterization tests is their ability to capture the subtle details of a system that aren't immediately apparent from class or method names alone.

For example, consider a method in an order processing system that calculates the total order amount and applies discounts. A characterization test for this method would verify that the current logic correctly calculates the total and applies discounts as expected, even if the logic is flawed. This way, we can confidently refactor the code, knowing that the test will alert us if the behavior changes unexpectedly.

Without tests, it's difficult to understand the code's behavior, making modifications risky. Characterization tests offer a solution by allowing us to explore and document the code's behavior safely. By writing tests that capture the current functionality, we create a baseline that helps identify unintended changes during future modifications.

Writing characterization tests involves creating tests that reflect the current behavior of the code. Let's look at a practical example using the OrderProcessor class from our order processing system. Suppose we have a method that processes orders and applies discounts based on the total amount:

In the above test, we arrange an order with a total amount that qualifies for a bulk discount. The test then verifies that the discount is applied correctly, capturing the current behavior of the method.

When writing characterization tests, it's important to follow best practices to ensure their effectiveness. First, we should focus on capturing the current behavior accurately, even if it includes known issues. The goal is to document what the code does, not what it should do.

Additionally, we must maintain test quality by writing clear and concise tests that are easy to understand and maintain. Incremental testing is also crucial; we should start with simple tests and gradually cover more complex scenarios as we gain confidence in the system's behavior.

Lastly, we should think of good names for the tests. Since they should describe the system as it is now, the names themselves should reflect the particular facet of character we are trying to capture and describe. We could name our tests Test1, Test2 and so on, but this would be unhelpful and confusing to other people looking at the tests. We want to supply a way of explaining, at a glance, what the test is doing and what the expectations are.

In this lesson, we've explored the concept of characterization tests and their role in increasing code coverage. By documenting the current behavior of a system, these tests provide a safety net for future changes and facilitate a deeper understanding of the code. As we move on to the practice exercises, we'll have the opportunity to apply these concepts and write characterization tests for an order processing system.

We should keep in mind that the order processing logic might seem "wrong" at times, but we must resist the urge to "fix" these problems! It's important to remember that characterization tests are meant to document the existing behavior of a system, not adjust flaws in the logic.

This hands-on experience will reinforce our understanding and enhance our skills in increasing code coverage. Good luck, and happy testing!