Testing classes in isolation and with mocks is popular. But those tests have drawbacks like painful refactorings and the untested integration of the real objects. Fortunately, it’s easy to write integration tests that hit all layers. This way, we are finally testing the behavior instead of the implementation. This post covers concrete code snippets, performance tips and technologies like Spring, JUnit5, Testcontainers, MockWebServer, and AssertJ for easily writing integration tests. Let’s discover integration tests as the sweet spot of testing.
MongoDB’s dynamic schema is powerful and challenging at the same time. In Java, a common approach is to use an object-document mapper to make the schema explicit in the application layer. Kotlin takes this approach even further by providing additional safety and conciseness. This post shows how the development with MongoDB can benefit from Kotlin and which patterns turned out to be useful in practice. We’ll also cover best practices for coding and schema design.
At a first glance, in-memory databases (like H2 or Fongo) look like a good idea. You can test your code without having to worry about installing and managing a dedicated database server up front. Just start your tests and the H2 database will be up and running. However, this comfort comes with severe drawbacks. In this post, I explain my reservations and point out Docker as an alternative which can be easily used with TestContainers or within the Gradle/Maven build.