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We write a single integration test which tests all four classes together. For details on this, check out the post ‘Don’t use In-Memory Databases (H2, Fongo) for Tests’. Moreover, you can easily run into situations where you can’t use (or test) a certain (database-specific) feature because the in-memory database doesn’t support it or act differently. So a green in-memory-database-based test is absolutely no guaranty for the correct behavior of your application in production. The in-memory database and the database used in production behave differently and may return different results. Using an in-memory database for tests also reduces the reliability and scope of our tests. In-Memory Database != Production Database. In general, we have to write and maintain multiple test classes. Most likely, all tests will not compile anymore and we have to adapt them all. Imagine, we change the internal data structure ProductEntity that is returned from the ProductDAO back to the ProductController and then passed on to the TaxServiceClient and the PriceCalculator. Refactorings can become a horrible nightmare. Therefore, changing this implementation leads to broken tests and a lot of work to fix these tests. Mock-based tests are tightly coupled to the implementation of the application. It’s easy to forget to write those unit tests. 
For instance, the ProductDAO may return null if no product was found, but the TaxServiceClient expect that the product is not null. I experienced many times that mistakes are happening exactly in the integration of the real classes. We are not testing close enough to reality. Green mock-based unit tests don’t mean that our service works correctly in production because we never test if the real classes are working together correctly. Unreliable tests and limited test scope.The PriceCalculatorTest is straight-forward as the PriceCalculator doesn’t have any dependencies.Often, we use some kind of mock server like MockWebServer or WireMock.
The TaxServiceClient tests the remote call logic in the TaxServiceClient. A popular approach is to use in-memory databases like H2 or Fongo. The ProductDAOTest tests the database access logic in the ProductDAO. ProductControllerTest: In order to test the ProductController in isolation, we have to mock all used classes: the ProductDAO, the TaxServiceClient, and the PriceCalculatorMock. “Test your classes in isolation and control its dependencies with mocks or stubs”.įour unit tests for testing each class in isolation and with mocks. Isolated Mock-Based Unit TestsĪ typical solution for testing is to test every class in isolation. Multiple classes, a database, and a remote system are involved. Our class composition might look like this: This resource retrieves the product data from a database, requests tax information from a remote service and executes some price calculation logic. Let’s assume we like to write the HTTP resource /products. 
If you don’t like to use the term “integration test” for the proposed testing style you may prefer the term “component test”. They are a good compromise between setup effort and production-closeness. For me, the proposed integration tests are the sweet spot of testing. Test against the real database (via testcontainers) instead of an in-memory-database to be even closer to production. Refactorings in the internal structure are less likely to break your tests. Higher test coverage as we test both the parts and everything as a whole. We test much closer to reality because in production the application will also use the real objects. 
We test behavior instead of an implementation.Instead, focus more on integration tests in which we wire the real objects together and write a single test that hits all layers.We don’t test if the classes are working together correctly.Traditional mock-based unit tests are testing classes in isolation.Let’s discover integration tests as the sweet spot of testing.
Mockwebserver enqueue code#
This post covers concrete code snippets, performance tips and technologies like Spring, JUnit5, Testcontainers, MockWebServer, and AssertJ for easily writing integration tests. This way, we are finally testing the behavior instead of the implementation. Fortunately, it’s easy to write integration tests that hit all layers. But those tests have drawbacks like painful refactorings and the untested integration of the real objects. Testing classes in isolation and with mocks is popular. More Effort for Input Data Creation and Output Data Assertions.
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Java Ecosystem, Kotlin, Engineering Management, Sociology of Software Development Focus on Integration Tests Instead of Mock-Based Tests
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