Test Doubles 101: Mocks, Stubs, Fakes, and Virtual Services Explained

In the software testing world, crafting robust tests often involves isolating your code from external dependencies. This blog post delves into the concept of test doubles - Mocks, Stubs, Fakes, and Virtual Services - equipping you with a versatile toolkit to navigate these interactions seamlessly. We'll revisit the familiar banking application scenario to illustrate how each concept aids in test creation.

The Banking Application: A Familiar Testing Ground

Imagine a banker application used by bank staff to manage customer accounts. This application relies on a crucial dependency - the Customer API - to retrieve customer data for various functionalities. However, during testing phases, this API might be unavailable, under development, or cost-prohibitive to access. Test doubles come to the rescue by mimicking the behavior of the Customer API, allowing you to test your application in a controlled environment.

Mocks: Verifying Interactions, Not Responses

Mocks serve as simulated interfaces, mimicking APIs, databases, or web servers. Their primary focus is on ensuring your code calls upon them as expected, not necessarily the specific outputs they provide. Mocks are particularly useful in unit testing to isolate a unit of code and verify its interaction with the mock appropriately. They typically reside within the code itself and don't return values by default. However, in some cases, they might return pre-defined values to enable further code execution.

Key Points about Mocks:

• Interaction Focus: Ensures your code calls the mock as intended.
• Statefulness: Tracks how many times the mock is called and with what parameters.
• Limited Validation: Doesn't validate return values; primarily concerned with interactions.
• Development Team Usage: Primarily used by development teams for unit testing.
• Automated Creation: Frameworks like Mockito, JMock, and EasyMock simplify mock creation.

Stubs: Predefined Data for Predictable Behavior

Stubs are objects pre-loaded with data to simulate responses during tests. Unlike mocks, they don't emphasize interaction verification but rather provide controlled outputs. This is beneficial when you need to test how your code behaves with different data sets, representing success, failure, or various API responses. Stubs can be used to mock databases, returning specific data collections, or APIs, returning SOAP or JSON responses.

Key Points about Stubs:

• Predefined Data: Contains pre-determined data to provide predictable responses.
• Avoids Side Effects: Bypasses interactions with real data sources, preventing unintended consequences.
• Efficient Testing: Enables testing various code functionalities with different outputs.
• Tight Coupling: Tailored to specific tests, limiting reusability across teams.
• Hardcoded Values: Responses are typically hardcoded within the stub.

Fakes: Bridging the Gap Between Stubs and Mocks

Fakes offer a more comprehensive approach compared to stubs. They are closer to real-world implementations of the dependent system, enabling you to test more complex scenarios. Fakes can be implemented in two ways:

• Fake Classes: Mimic the real class behavior with methods that can process data and perform operations like balance calculations in our banking application example. This allows for testing functionality that relies on intricate interactions.
• Fake APIs: Standalone APIs that simulate the behavior of real APIs. These can be created using various tools or web applications and can respond with pre-defined data or even integrate with external services. Fake APIs are valuable for integration testing and performance testing.

Key Points about Fakes:

• Complex Scenarios: Handles intricate interactions and logic replicating real-world behavior.
• Two Implementations: Fake classes and fake APIs cater to different testing needs.
• Testing Versatility: Enables testing of system-level functionalities beyond unit tests.
• Potential Overhead: Creating and maintaining complex fakes can require more effort.

Virtual Services: Beyond Mocks and Stubs

Service virtualization is a powerful technique that goes beyond basic test doubles. It allows you to simulate the behavior of entire systems or components, offering several advantages:

• Behavior Simulation: Simulates various scenarios, like internet outages, to test application resilience.
• Test Data Management: Provides readily available test data, eliminating the need to rely on actual customer data.
• Performance Testing: Enables controlled performance testing by virtualizing APIs and measuring response times.
• Negative Testing: Creates rare scenarios using virtual services to test how the application handles edge cases.

Key Points about Virtual Services:

• Comprehensive Simulation: Simulates entire systems or components for broader testing.
• Improved Efficiency: Provides readily available test data and facilitates performance testing.
• Negative Test Cases: Enables creation of rare scenarios for robust testing.
• Resource-Intensive: Setting up and maintaining virtual services can involve more resources.