Writing unit tests for your application’s service layer is a waste of your time and won’t strengthen your application any better than functional tests would. Writing functional tests that thoroughly test your application does what it says it will do correctly is a much better use of your resources.
I first learned about test driven development (TDD) and automated testing in 2009 and was blown away. I immediately purchased the book xUnit Test Patterns and devoured it. I learned about code smells and fixtures and stubs and mocks and everything in-between. It was amazing that I could actually verify that my application works like I intended it to. Throw TDD in the mix where I could guarantee that I only write as much code as necessary to pass my tests and I was hooked.
I immediately took an academic approach to testing. Invert every components control, mock every depended on component (DoC), completely isolate and unit test everything: the database, other objects, even the file system.
For trivial applications like a project hacked together on a weekend, this practice was fine. I felt like I spent an equal amount of time writing tests as I did writing the code itself.
Fast forward a few years and I have a successful consultancy and am working full time writing web and network applications. I’m still trying to write unit tests and follow TDD principles, but it just isn’t working.
For example, I would write both unit and functional tests for my application’s controllers. For a Symfony application, this is a non-trivial task as the number of depended on components in each controller can easily force your tests to be longer than the controller code itself. Breaking controllers into very small units is difficult as they often deal with handling UI interactions and must communicate to multiple components of the application.
Application Development Has Evolved
When TDD and automated testing became integrated with object oriented programming, databases were big behemoths that required a full time team to manage. File systems were very slow and not reliable. It made sense that your tests should be comprised of small units that were tested in isolation: your components were unreliable!
Today, enterprise applications are contained in a single repository. You can mirror a production server on your insanely powerful laptop with a single
Vagrantfile. Working with databases in your tests is a cinch (especially with tools to build out your fixtures in YAML). In all but a few instances, you generally don’t need to worry about a network device or disk drive failing during test suite execution. And modern frameworks employ multiple environments with a dependency container that makes it very simple to mock complex components in your test suite.
Application development has evolved, and the time spent writing unit tests that mock every component in your system does not offer the same dividends as writing a simple functional or integration test does.
Lets look at a small example of how writing a simple functional test can rapidly increase development and still provide the same guarantees your code works.
If you recall from my previous article on using the ORM, I am in the process of building an importer for an online store. I have the code written, and now I want to verify it is correct (I’ve thrown any notion of TDD out of the window).
In the first example, all depended on components of the system under test (SUT) are mocked.
The first example is academic; it’s pure. It proves my code works, it’s fast, and it tests individual units. The second example is functional. I’m taking actual files, running them through my code, and seeing how the code responds.
Another benefit of the second example is that the data provider can grow over time. Client deliver a malformed file and you want to see how the code responds? Throw it in the provider. Client thinks there’s an issue with your importer because their file matches your spec? Throw it in the provider. It makes finding actual bugs that a unit test would completely ignore.
When to Write Unit Tests
There are, of course, times when writing unit tests is necessary and writing functional tests may be impossible.
If you are writing a library or framework, it is wise to write unit tests. You don’t know how your code will actually be used, so having formal verification that your library classes do what they say they will is a must. It also adds a great deal of built in documentation to your codebase because a passing test, by definition, accurately documents your code.
Another time to write unit tests would be for a legacy codebase right before a refactoring. If the codebase is old enough, your DoC’s may be very difficult to work with and thus writing a unit test will accurately capture the functionality of your application.
From the moment I started writing tests, I’ve attempted to get every developer at every company I’ve worked for to start writing tests without much luck. In retrospect, I feel if I had started with a “functional first” approach, I would have been more successful in my efforts. Introducing a developer to testing by way of writing simple functional tests may be the best bet to get all developers writing tests, period.