Last updated on Sep 23, 2024

How can you avoid common testing pitfalls with state pattern software?

State pattern software is a design pattern that allows an object to change its behavior based on its internal state, making it more flexible, maintainable, and readable. However, it also comes with some testing challenges. This article will discuss how to avoid common testing pitfalls with state pattern software, such as coupling tests with implementation details, testing transitions instead of outcomes, overlooking edge cases and invalid states, forgetting to mock dependencies and side effects, and overusing test doubles and losing confidence.

1 Coupling tests with implementation details

One of the main benefits of the state pattern is that it encapsulates the logic of each state and its transitions in separate classes, making them easy to modify and extend. However, this also means that your tests should not rely on the internal details of how each state is implemented, such as the names of the classes, the methods they call, or the fields they access. Instead, your tests should focus on the observable behavior of the object under test, such as the methods it exposes, the events it triggers, or the outputs it produces. This way, you can avoid brittle tests that break when you refactor or add new states.

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James Albert Silvoza

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I also use mock objects to simulate different state transitions, ensuring that edge cases and error-handling scenarios are covered. This helps maintain test coverage while avoiding the complexity of testing all possible state combinations directly.

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2 Testing transitions instead of outcomes

Another pitfall of testing state pattern software is to focus too much on the transitions between states, rather than the outcomes of those transitions. For example, you might be tempted to write tests that verify that a certain method call changes the state of the object from A to B, or that a certain event causes the object to enter state C. However, these tests are not very useful, because they do not tell you anything about the behavior of the object in each state, or the effects of those transitions on the system. Instead, you should write tests that assert the expected outcomes of each state and transition, such as the return values of the methods, the state of the data, or the interactions with other components.

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3 Ignoring edge cases and invalid states

A common mistake when testing state pattern software is to assume that the object under test will always be in a valid and expected state, and to ignore the edge cases and invalid states that might occur. For example, you might forget to test what happens when the object receives an unexpected input, when it encounters an error, when it reaches a terminal state, or when it needs to revert to a previous state. These scenarios can lead to bugs, crashes, or inconsistent behavior, so you should always test them and handle them gracefully. You can use tools like state diagrams, state tables, or boundary value analysis to identify and cover all the possible states and transitions of your object.

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4 Forgetting to mock dependencies and side effects

State pattern software often depends on external components or resources, such as databases, APIs, files, or timers, to perform its tasks and change its state. These dependencies can introduce variability, complexity, and slowness to your tests, making them unreliable, hard to control, and slow to run. Therefore, you should always mock these dependencies and isolate your object under test from them. This way, you can simulate different scenarios and inputs, verify the interactions and outputs, and speed up your tests. You should also mock any side effects that your object might cause or observe, such as logging, notifications, or events, and assert that they are executed correctly and at the right time.

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5 Overusing test doubles and losing confidence

When testing state pattern software, it is essential to mock dependencies and side effects; however, you should also be mindful not to overuse test doubles such as stubs, spies, or fakes. Test doubles can simplify and isolate tests; however, they can also lead to unrealistic or inconsistent scenarios that do not reflect the real behavior of the system, hide errors or bugs that may occur in the actual dependencies or side effects, make tests too specific or too generic, and increase maintenance cost and complexity. To avoid these risks, use test doubles sparingly and wisely and balance them with some integration tests that use real components or resources. Doing so will help you increase confidence and coverage while ensuring that your state pattern software works as expected in different contexts and environments.

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