CategoryUnit Testing

Unit, integration, end-to-end tests: do I need all of them?

Yes. I mean, don’t even think about it. You’ll need all of them, probably in different measures, but there is no “we shipped to production without tests”.

Tests are the first rampart separating you from madness and failure.
Why madness? Try to do even a small refactoring after you’ve deployed your app. Without automatic tests you’ll have to manually probe the entire system (or systems if you’re on microservices).

Why failure ? Simple, just think on the long run. Maintenance will quickly become a hell and adding new features will soon bring you to the infamous “it’s better if we re-build this from scratch”.

So! Where should we start? From the pyramid!

the test pyramid

The test pyramid. Image taken directly from Martin Fowler’s article. Thanks, Martin.

Starting from the bottom, you’ll begin with writing the unit tests. “Unit” here means that you’re testing a single small atomic piece of your system, a class, a function, whatever. You won’t connect to any external resource (eg. database, remote services) and you’ll be mocking all the dependencies. 
So, ideally you’ll be checking that under specific circumstances a method is throwing an exception or the cTor is populating the class properties or the result of a computation is a specific value giving a controlled input.
Also, unit tests have to be extremely fast, in the order of milliseconds, giving you a very quick and generic feedback of your system.

Next is the “Service” layer or, more commonly, “Integration”. This is where things start to get interesting. Integration tests check that two or more pieces fit correctly and the cogs are oiled and greased.  So stuff like your Persistence layer, access to the database, ability to create or update data and so on. They might take more time than  unit tests and probably will be in a lesser number, but their value is extremely high.

Then we have the “UI” or “end-to-end” tests. Here we’re making sure that the whole system is working, inspecting from the outside, with little to none knowledge of the inner mechanism. You’ll be checking that your API routes are returning the right HTTP statuses, setting the proper headers and eating the right content types.

In the end it’s all a matter of perception. The point of view is moving from the inside of the system, the developer perspective, to the outside: the consumer perspective.

There are of course other typologies of tests, acceptance, smoke, functional and so on. But if you begin adding the coverage using this pyramid you’ll save an awful lot of headaches and keep your system maintainable and expandable.

How to reset the entities state on a Entity Framework Db Context

I had two bad days. Those days wasted chasing a stupid bug. I had a test class with 4 test cases on my infrastructure layer. If executed one by one, they pass. If the whole suite was executed, only the first one was passing.

At the end I found out that it was due to the Entity Framework Core db Context tracking the state of the entities. More or less. 
In a nutshell, every time a call to SaveChanges() fails,  the subsequent call on the same instance of the db context will retry the operations. 

So let’s say your code is making an INSERT with bad data and fails. Maybe you catch that and then you do another write operation reusing the db context instance.

Well that will fail too. Miserably.

Maybe it’s more correct to say that the second call will look for changes on the entities and will try to commit them. Which is basically the standard and expected behaviour.

Since usually db context instances are created for every request this might not be a big issue.

However, in case you are writing tests using XUnit Fixtures, the instance is created once per test class and reused for all the tests in that class. So in this case it might affect test results.

A potential solution is to reset the state of the changed entities, something like this:

Another option is to avoid entirely reusing the db context and generating a new one from scratch.
In my code the db context was registered on the DI container and injected as dependency. I changed the consumer classes to use a Factory instead and that fixed the tests too 🙂

Unit testing MongoDB in C# part 4: the tests, finally

More than a year. Wow, that’s a lot, even for me! In the last episode of this series we discussed about how to create the Factories for our Repositories. I guess now it’s time to put an use to all those interfaces and finally see how to unit test our MongoDB repositories 🙂

Remember: we are not testing the driver here. The MongoDB team is responsible for that. Not us. 

What we have to do instead is to make sure all our classes follow the SOLID principles and are testable. This way we can create a fake implementation of the low level data access layer and inject it in the classes we have to test. Stop.

Let’s have a look at the code:

In our little example here I am testing a CQRS Command Handler, the one responsible for creating a user. Our handler has an IDbContext as dependency, which being an interface allows us to use the Moq Nuget package to create a fake context implementation. 

Also, we have to instruct the mockDbContext instance to return a mock User Repository every time we access the .Users property.

At this point all we have to do is to create the sut, execute the method we want to test and Verify() our expectations. 

Let’s make a more interesting example now:

Now that we have created the user, we may want also to update some of his details. The idea here is to instruct the mockRepo instance to return a specific user every time the FinstOneAsync method is executed.

Again, now we just need to verify the expectations and we’re done!

Note that in this case we are making an assumption about the inner mechanism of the Handle() method of the UpdateUserHandler class. Personally I tend to stick with Black Box Testing, but sometimes (eg. now) you might be forced to use White Box Testing instead. If you don’t know what I am talking about, there’s a nice article here you may want to read.

 

CQRS: on Commands and Validation

Let’s have a quick discussion about CQRS. There’s a lot to say to be honest, so let’s try to focus on just one thing today: validating your Commands (who knows, I could start a series after this, we’ll see).

The idea is simple: how can I make sure that the data I am passing to my Command Handler is valid?

Also, what is the definition of “valid” ?

There are several aspect to take in consideration, several “levels” of validation. I could just make sure the Command object is not null and/or the data it contains is not empty. Or I could run the validation against some kind of context and check the application Business Rules.

As you can imagine, having different levels means that we could have different implementations scattered in various places/layers of our architecture. For example I could have the API Controller (or whatever outmost layer you have) check for null and perform some Business Context validation later, before or directly in the Command Handler.

In my last project however, I decided to keep things simple and keep my validation in just one place.

Initially the right spot was the Command Handler itself, but of course this would have violated the SRP.

A quick and immediate solution was to have a separate instance of a IValidator<TCommand> injected in the handler. Easy.

Then I realised that my handlers are more “close to the metal” than expected: in most of the cases they access directly the DAL (passing through some kind of IDbContext) and I didn’t wanted to rewrite the call to the IValidator in case I had to switch the persistence layer.

Luckily enough, there’s a nice pattern that came into rescue: the Decorator! As explained very clearly on the SimpleInjector docs, you can create a ValidationCommandHandlerDecorator class, inject an IValidator<TCommand> and let your IoC do the rest.

Maaaaagic.

Bonus tip: in some cases you may want to skip completely the validation. Maybe you have a very good reason or maybe you’re just lazy. Whatever.

In this case, all you have to do is to write some kind of NullValidator<TCommand> class and instruct your IoC to use it when a specific validator is missing for that Command.

Unit testing MongoDB in C# part 3: the database factories

Welcome to the third article of the series!

Last time I was talking about the database context and at how I injected a Factory to create the repositories. Of course we could have injected every single repository in the cTor, but this way adding a new collection to the database would force too many changes.

Injecting just the factory instead allows us to create internally all the repositories we need, add new ones easily and of course makes our life easier when it comes to testing.

Let’s take a look at our Repository Factory interface:

as you can see, that’s very standard and easy. The implementation also is pretty straightforward:

A couple of notes on this:

  1. the RepositoryOptions class is just a simple Value Object encapsulating some details like the connection string and the name of the collection
  2. in the cTor we have a dependency on another Factory used to get a reference to the database. Why we do this? I guess you know the answer 😀

As you can see, this injected Factory also is very easy:

you can find the implementation here.

Next time: let’s write some tests!

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