Unit Testing the fetchDataset Endpoint

A comprehensive guide to unit testing your Spring Boot REST controller

Highlights

Using Spring Testing Annotations: Employ @WebMvcTest and @MockBean for an isolated web test.
Handling Asynchronous Behavior: Utilize reactive tools and verification to test subscription callbacks.
Verifying Service Interaction: Ensure that the mocked service is called as expected with the correct parameter.

Introduction

In this comprehensive guide, we will demonstrate how to create a unit test for the REST controller endpoint that exposes the "/fetch-dataset" GET endpoint. The endpoint uses a service method, "fetchDatasetFromJson", which returns a reactive Mono. The implementation subscribes to the Mono and logs the parsed dataset. Although the endpoint always returns a 200 OK status, it is crucial to validate the service call, ensuring that any asynchronous operations are performed as intended.

Testing Environment Setup

Key Components and Dependencies

For this unit test, we use the following components:

@WebMvcTest: This annotation focuses on the controller layer and avoids loading the entire Spring context.
@MockBean: It creates mock instances of the dependent services, such as 'aggregateDatasetService', so that we can control their behavior and isolate the controller logic.
MockMvc: A simulation API that allows crafting HTTP requests to test the controller without starting an actual server.
Mockito: This is used to set expectations on the behavior of the mocked service, ensuring it returns the desired outcomes during tests.

The combination of these components provides a fast and focused unit testing environment for Spring Boot REST controllers.

Writing the Unit Test

Test Class Design

The test will be structured using a JUnit 5 test class annotated with @WebMvcTest to specify the controller under test. The service is mocked with @MockBean, and MockMvc is used to simulate the HTTP call to the endpoint. One of the key aspects is that our controller method, although asynchronous in nature because it calls subscribe on the Mono, still returns an HTTP 200 status synchronously. Hence, the test will focus on verifying the status code and ensuring that the service method is invoked with the expected parameter.

Test Code Example


  // Import necessary classes and annotations
  import static org.mockito.Mockito.verify;
  import static org.mockito.Mockito.when;
  import static org.springframework.test.web.servlet.request.MockMvcRequestBuilders.get;
  import static org.springframework.test.web.servlet.result.MockMvcResultMatchers.status;

  import org.junit.jupiter.api.BeforeEach;
  import org.junit.jupiter.api.Test;
  import org.mockito.InjectMocks;
  import org.mockito.Mock;
  import org.mockito.MockitoAnnotations;
  import org.springframework.beans.factory.annotation.Autowired;
  import org.springframework.boot.test.autoconfigure.web.servlet.WebMvcTest;
  import org.springframework.boot.test.mock.mockito.MockBean;
  import org.springframework.http.MediaType;
  import org.springframework.test.web.servlet.MockMvc;
  import reactor.core.publisher.Mono;

  // Import your controller and service packages as necessary
  // Assume YourController is the class that defines the fetchDataset method
  // and AggregateDatasetService is the dependency service.

  @WebMvcTest(YourController.class)
  public class YourControllerTest {

      @Autowired
      private MockMvc mockMvc;

      @MockBean
      private AggregateDatasetService aggregateDatasetService;

      @BeforeEach
      public void setUp() {
          // Ensure that mocks are initialized before each test if necessary.
          MockitoAnnotations.openMocks(this);
      }

      @Test
      public void testFetchDataset_SuccessfulCall() throws Exception {
          String datasetJsonUrl = "https://example.com/dataset.json";
          
          // Create a dummy object for the expected dataset
          Object expectedDataset = new Object(); // Replace with an actual dataset object if available
          
          // Define mock behavior: when the service method is called, return a Mono containing the expected dataset.
          when(aggregateDatasetService.fetchDatasetFromJson(datasetJsonUrl))
              .thenReturn(Mono.just(expectedDataset));

          // Perform a GET request using MockMvc to test the endpoint.
          mockMvc.perform(get("/fetch-dataset")
                  .param("datasetJsonUrl", datasetJsonUrl)
                  .contentType(MediaType.APPLICATION_JSON))
                  .andExpect(status().isOk());

          // Verify that the service method was indeed called with the provided URL.
          verify(aggregateDatasetService).fetchDatasetFromJson(datasetJsonUrl);
      }
  }

In this test case:

The endpoint is invoked with a valid dataset URL.
The service is set up to return a simple Mono with a dummy dataset.
We check that the status returned is 200 OK.
The interaction with the mocked service is verified to ensure correct parameters are passed.

Handling Asynchronous Behavior

Despite using subscribe() to trigger the asynchronous call in the controller, the test does not need to wait for the asynchronous processing to complete, as the HTTP status is synchronous. However, should the operation need deeper validation such as logging or side effects on the response body, additional techniques (like using StepVerifier for reactive streams) might be considered. In the current context, the crucial part is ensuring that the service is called as expected.

Expanding Tests for Edge Cases

Dealing with Invalid URL or Service Errors

While the primary test ensures a successful path, additional scenarios can be developed:

Invalid URL: If the "datasetJsonUrl" is not in a valid format, the controller may potentially return a bad request (HTTP 400) if validation is built into the endpoint. To test such a case, craft a test where the invalid URL is provided and assert that the endpoint responds appropriately.

Service Error: Simulate cases where the service returns an error (for example, a Mono.error() call). In this scenario, test that the endpoint might gracefully handle the error by returning a HTTP 5xx status code. Although our default implementation always returns OK, a fully implemented error handling strategy should be verified.

Additional Test Cases - A Comparison Table

Scenario	Description	Expected Outcome
Successful Call	Valid dataset URL provided and service returns a dataset.	HTTP 200 OK, service method called with correct parameter.
Invalid URL Format	Provided URL is not correctly formatted.	HTTP 400 Bad Request (if URL validation exists).
Service Error	The service call results in an error due to unexpected conditions.	HTTP 5xx error status (if error handling is implemented).

Advanced Integration with Reactive Testing (Optional)

In scenarios where the controller's asynchronous processing needs to be validated in detail, developers can integrate reactive testing utilities such as StepVerifier from Project Reactor. For instance, if the response body contained data derived from the asynchronous operation, StepVerifier could be employed to assert on each element emitted. However, in our current case, since the endpoint uses subscribe merely for logging and returns an empty ResponseEntity immediately, the traditional synchronous verification suffices.

Integration with Build Tools

Maven Dependencies

Ensure your project's build file includes the necessary dependencies for testing with Spring Boot and Mockito. Here is an example snippet for a Maven-based project:


  <!--
      Dependency for Spring Boot Testing
  -->
  <dependency>
      <groupId>org.springframework.boot</groupId>
      <artifactId>spring-boot-starter-test</artifactId>
      <scope>test</scope>
  </dependency>
  <dependency>
      <groupId>org.mockito</groupId>
      <artifactId>mockito-junit-jupiter</artifactId>
      <scope>test</scope>
  </dependency>

With these dependencies, you ensure that the testing framework and mocking libraries are available and configured appropriately.

Continuous Integration and Testing

Incorporating these unit tests within your continuous integration (CI) pipeline ensures that the functionality of your controller remains intact as the code evolves. Automated tests are executed with each commit, providing timely feedback and reducing the chance of regressions.

Best Practices for Testing Asynchronous Methods

Isolating Dependencies

It is a best practice in unit testing to isolate the component under test. Make use of mocking frameworks like Mockito to ensure that only the behavior of the controller is in scope. This avoids unnecessary complexity and potential side effects from external dependencies such as asynchronous service calls.

Verifying Side Effects

Although the controller logs the result, you can verify that however the asynchronous processing is structured (for example, through a side-effect mechanism), the service interactions are consistently maintained. Keep tests focused on observable outcomes, such as HTTP response statuses and invoked service methods.

Extensible Testing Scenarios

When designing unit tests, consider additional scenarios:

Null Dataset: Validate how the controller handles cases where the service returns a null or empty Mono.
Multiple Requests: Ensure repeated calls to the endpoint behave consistently, especially under load simulations.
Error Propagation: Verify that any exceptions thrown by the service are gracefully handled without exposing sensitive information to the client.