Code-Held

When working with JPA I prefer generating the primary key on the application and not in the database (check out this post from James Brundege). Additionally, I also prefer optimistic locking and in order to use it you need to specify a @Version field in your Entity. But you need to be careful how to initialize these two fields. In this post I’ll talk about an error when you assign a default value for both fields in JPA which leads the EntityManager to never call persist but the merge operation instead when creating a new entity.

Last week I reviewed the data design of a colleague. He had to improve a feature and while working on it he noticed that the existing design was not sufficient to properly reflect the changes he had to do. Intuitive he followed the practices of other models in the code and introduced an enumeration to distinguish between different alert types that can be created in the application. Using an enumeration for it is not the optimal solution and in this post I want to describe why you should always question when you see an enumeration in your code and think about solving it with polymorphism instead.

In a project I worked on I saw that nearly every entity and value object was created with Lomboks @Builder. Their reason is that it makes it easier to construct these objects - especially for tests. But it comes with a cost. The problems that these builders create can’t be detected by the compiler and are especially dangerous in every CI environment.

Unit tests had a bad reputation in many teams I worked with. To my confusion I even experienced that a team wrote a hell lot of integration tests but rarely any unit tests. This is contrary to the well-known testing triangle, and surprised me quite a bit. The reason - as I was told - was the experience of the team. “When you change something you have to adapt many unit tests”, was the common tenor. So they decided to write integration tests which call the real endpoints instead. This comes with a cost. Generally you have a harder time to identify where a issue lies when an integration test - which goes through the whole system - fails. Also the runtime will not lead to fast feedback - one of the main benefits of having proper unit tests. I discovered that the issue is that many developers never learned how to write proper unit tests. In this post I will cover the best practices that I developed throughout my career.

Spring Data provides an easy way of keeping track who creates and modifies a persistent entity as well as when the action happened by annotating properties with @CreatedBy, @CreatedDate, @LastModifiedBy and @LastModifiedDate. The properties are automatically provided by an implementation of the AuditAware and DateTimeProvider interface.

I work with Jenkins Pipeline for three years now and one pain point is proper isolation of shared functionality between pipelines but even steps. In our repository we defined multiple pipelines and some are that large that we share functionality within it. Jenkins offers the possibility to create shared libraries for that purpose. But unfortunately it’s not possible to load it from the same repository. Since many of the changes in the pipeline are related to a change of the shared library it was tedious to match the branches and versions to be backward compatible. What we actually wanted is having the shared library in our main repository so the states of the pipeline is pinned to the state of the main repository. And we finally figured out how to do (hack) that.