The goal of your testing strategy

ayende Blog

I run across this article, which talks about unit testing. There isn’t anything there that would be ground breaking, but I run across this quote, and I felt that I have to write a post to answer it.

The goal of unit testing is to segregate each part of the program and test that the individual parts are working correctly. It isolates the smallest piece of testable software from the remainder of the code and determines whether it behaves exactly as you expect.

This is a fairly common talking point when people discuss unit testing. Note that this isn’t the goal. The goal is what you what to achieve, this is a method of applying unit testing. Some of the benefits of unit test, are:

Makes the Process Agile and Facilitates Changes and Simplifies Integration

There are other items in the list on the article, but you can just read it there. I want to focus right now on the items above, because they are directly contradicted by separating each part of the program and testing it individually, as is usually applied in software projects.

Here are a few examples from posts I wrote over the years. The common pattern is that you’ll have interfaces, and repositories and services and abstractions galore. That will allow you to test just a small piece of your code, separate from everything else that you have.

This is great for unit testing. But unit testing isn’t a goal in itself. The point is to enable change down the line, to ensure that we aren’t breaking things that used to work, etc.

An interesting thing happens when you have this kind of architecture (and especially if you have this specifically so you can unit test it): it becomes very hard to make changes to the system. That is because the number of times you repeated yourself has grown. You have something once in the code and a second time in the tests.

Let’s consider something rather trivial. We have the following operation in our system, sending money:

image

A business rule says that we can’t send money if we don’t have enough in our account. Let’s see how we may implement it:

This seems reasonable at first glance. We have a lot of rules around money transfer, and we expect to have more in these in the future, so we created the IMoneyTransferValidationRules abstraction to model that and we can easily add new rules as time goes by. Nothing objectionable about that, right? And this is important, so we’ll have unit tests for each one of those rules.

During the last stages of the system, we realize that each one of those rules generate a bunch of queries to the database and that when we have load on the system, the transfer operation will create too much pain as it currently stand. There are a few options that we have available at this point:

  • Instead of running individual operations that will each load their data, we’ll do it once for every one. Here is how this will look like:

As you can see, we now have a way to use Lazy queries to reduce the number of remote calls this will generate.

  • Instead of taking the data from the database and checking it, we’ll send the check script to the database and do the validation there.

And here we moved pretty much the same overall architecture directly into the database itself. So we’ll not have to pay the cost of remote calls when we need to access more information.

The common thing for both approach is that it is perfectly in line with the old way of doing things. We aren’t talking about a major conceptual change. We just changed things so that it is easier to work with properly.

What about the tests?

If we tested each one of the rules independently, we now have a problem. All of those tests will now require non trivial modification. That means that instead of allowing change, the tests now serve as a barrier for change. They have set our architecture and code in concrete and make it harder to make changes.  If those changes were bugs, that would be great. But in this case, we don’t want to modify the system behavior, only how it achieve its end result.

The key issue with unit testing the system as a set of individually separated components is that concept that there is value in each component independently. There isn’t. The whole is greater than the sum of its parts is very much in play here.

If we had tests that looked at the system as a whole, those wouldn’t break. They would continue to serve us properly and validate that this big change we made didn’t break anything. Furthermore, at the edges of the system, changing the way things are happening usually is a problem. We might have external clients or additional APIs that rely on us, after all. So changing the exterior is something that I want to enforce with tests.

That said, when you build your testing strategy, you may have to make allowances. It is very important for the tests to run as quickly as possible. Slow feedback cycles can be incredibly annoying and will kill productivity. If there are specific components in your system that are slow, it make sense to insert seams to replace them. For a example, if you have a certificate generation bit in your system (which can take a long time) in the tests, you might want to return a certificate that was prepared ahead of time. Or if you are working with a remote database, you may want to use an in memory version of that. An external API you’ll want to mock, etc.

The key here isn’t that you are trying to look at things in isolation, the key is that you are trying to isolate things that are preventing you from getting quick feedback on the state of the system.

In short, unless there is uncertainty about a particular component (implementing new algorithm or data structure, exploring unfamiliar library, using 3rd party code, etc), I wouldn’t worry about testing that in isolation. Test it from outside, as a user would (note that this may take some work to enable that as an option) and you’ll end up with a far more robust testing infrastructure.

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