Skip to main content

Simple code: Integration tests

Integration test is something that tests a functionality that is dependant on a external system e.g. a database, HTTP API or message queue.

Integration vs unit tests

The line is thin in my opinion. The integration part can be faked or a embedded services can be used in place of the actual integration point and with these solutions the interaction with the external system is bounded in the test context and the tests can be executed in isolation so they are very much like unit tests. The only difference with this type of integration test and unit test is that the startup time of the embedded or faked system usually takes some seconds and that adds total execution time of the tests. Even though the total test exection time is longer all the tests need to pass and all the cases need to be covered whether there's external systems involved or not so the importance is equal between the test types.

This is why I wouldn't separate unit and integration tests from each other within the code base but treat them as equal.

If there's a need to run a smaller set of tests while developing I'm quite sure all test libraries or IDE's support running tests by giving some type of filter so that the whole test suite doesn't need to be run every time a change is made if that's the goal of the separation.

Fakes

Fakes are a great way to test the logic of the application without actually interacting with a external system. A good example of a fake implementation is a memory based hashmap that can be a good enough fake implementation of a database.

Embedded services

Embedded services i.e. services that are started in the test code and stopped by the test code are a good option when testing integration of systems with automated tests but they don't neccessarily provide all the functionalities and capabilities of a real system so there's usually always the edge cases where embedded services are not viable.

Containers

Containers what most of use recognize as docker containers also provide a good solution for running tests that need to interact with external services. In my opinion this is probably the best way to tackle this issue though it's not as fast as fakes and embedded services and it does make your tests dependant on the containers but I think it's worth the extra running time and dependency.

Next part

In the next part I'll be writing of another test aspect i.e. acceptance testing.

Popular posts from this blog

Simple code: Naming things

There are two hard things in programming and naming is one them. If you don't believe me ask Martin Fowler https://www.martinfowler.com/bliki/TwoHardThings.html . In this post I'll be covering some general conventions for naming things to improve readability and understandabilty of the code. There are lots of things that need a name in programming. Starting from higher abstractions to lower we need to name a project, API or library, we probably need to name the source code repository, when we get to the code we need to name our modules or packages, we give names to classes, objects, interfaces and in those we name our functions or methods and within those we name our variables. Overall a lot of things to name. TLDR; Basic rule There's a single basic convention to follow to achiveve better, more descriptive naming of things. Give it a meaningful name i.e. don't use shorthands like gen or single letter variables like a, x, z instead tell what it represents, what it does...

Simple code: Simplicity

Simplest solutions are usually the best solutions. We as software developers work with hard problems and solve a lot of small problems every day. Solving a hard problem itself is a hard job. Though in my opinion it's not enough to solve a hard problem in any possible way but a hard problem should be solved with a simple solution. When a developer comes up with a simple solution to a hard problem then they can declare the problem solved. First a disclaimer. Coming up with a simple solution to a hard problems is itself a very hard problem and takes a lot of time, effort and practice. I've seen my share of "clever" solutions for hard problems and the problem with those is that usually the solution itself is so hard to understand that depending on the size of the problem it may take a developer from hours to days or even weeks to understand how that "clever" solution works. It's a rare occasion when a developer has come up with a simple solution to a hard pr...