Master The 5 Types of Mocks

What is a Mock, Fake, Spy, Stub and Dummy?

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Motivation

The 5 test doubles - created by Multiplayer

Mocks, often referred to as test doubles, are one of the most misunderstood and misused concepts in testing. Many developers use them without fully understanding their purpose, leading to brittle and unreadable tests that are hard to maintain.

Gaining a deeper understanding of test doubles—mocks, stubs, spies, fakes, and dummies—enables you to write cleaner, more effective tests, improving both the quality and reliability of your test suite.

Let's explore when and how each of these can be utilized, demonstrated through a real-life example:

Example service to test

To understand 5 types of test doubles, let's consider a real-life scenario where we want to write tests for the following UserService:

UserService dependencies - created by Multiplayer

The UserService has three dependencies:

• Datadog Logger: external service for logging

• User Repository: for storing our entries in the database

• Wage API: an external service to calculate wages for users

Now, let's see which test doubles we can use to mock out these dependencies:

Dummy

Dummies are used only for the initialization, without having any behavior. They act like placeholders, required to set up the system under test (SUT). With a dummy, we can convey our intent that the object is not directly used in the test context.

Dummies have two main forms:

• Dummy values: used as simple value replacements in data fields

• Dummy objects: used for more complex data types and dependencies

In our real-life example, dummies can be used for any functions of the UserService that don’t use the logger directly but are still needed for the initialization of UserService class:

Dummy - created by Multiplayer

Stub

A stub is a slightly smarter test double than a dummy as it can return some value. They are used to simulate incoming interactions, like returning hardcoded data for our SUT. A test stub is an implementation of an interface, provides a response to the system.

UserService uses an external API to calculate the wages of the users. To isolate our code from this API, we can create a stub that returns some hardcoded wage data, allowing us to focus on the business logic of our UserService:

Stub - created by Multiplayer

Spy

A test spy is almost like a real spy from a government who silently obtains information. But instead of obtaining information from a competitor, a test spy gathers internal information from dependencies. A spy is a special kind of test double that can record and verify internal behaviors.

In our UserService, if we are interested in how many times a function has been called, we could use a spy to collect and validate the behavior:

Spy - created by Multiplayer

Mock

A Mock is a powerful beast, yet it is often the most misused. It can pre-record expectations and have configurable behaviors. Serving as a proxy for the dependency, it allows us to verify outgoing interactions, such as ensuring that a method is called with specific parameters.

Mocks can be usually created by 3rd party libraries in most languages. Although they're flexible with a lot of utilities, the syntax of using them can be quite cryptic, making the tests less readable.

For our UserService, we could completely mock out the UserRepository, so that we can test our business logic in isolation:

Mock - created by Multiplayer

Fake

A fake is a simplified and lightweight implementation of a dependency. Seemingly it behaves as a real dependency, but it just emulates business rules. Unlike mocks, they're used for verifying state rather than interactions. As they're the closest to real implementations, they're also the most powerful ones for simulating system behaviors.

For our UserService, we can simulate the behavior of the UserRepository by creating a fake implementation. The advantage is that your tests will be less coupled to implementation details, resulting in more robust tests that aid refactoring:

Fake - created by Multiplayer

Summary

Picking the right test double is not a one-size-fits-all. It always depends on the context, type of application, type of tests, and the specific interactions you need to verify.

The choice should be guided by what you aim to achieve with your test. Ultimately, the goal is to create tests that are both effective and maintainable, providing confidence in your code without adding unnecessary complexity.

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