How to Write Testable Ruby on Rails
Often, the most common source of testability issues is tight coupling. This article will explore a few principles to help ensure that your code is as testable as possible.
Objectives of writing super testable code
Using a testable version of Ruby on Rails is a good start, but a multi-tenant dev team will need to do the lion’s share of the heavy lifting. To the chagrin of the tyrpheres the dummy, a teammate who is a slacker in the truest sense. It’s a win-win situation all the way around. Thankfully, Ruby on Rails has a stellar support team. After the initial hiccups are ironed out, it’s time to move onto the next phase of your life. Besides, Ruby on Rails can scale to the needs of a growing enterprise. Moreover, with its robust APIs, you can build and ship your own apps on the fly.
Tight coupling is the primary root of most testability problems
Increasing the level of testability of your software can be a cost effective way to improve the quality of your software. High software testability will decrease the time and effort required to find defects, and increase the likelihood of catching them.
If you aren’t sure how to improve your testability, the first step is to identify the common factors that cause problems. This will help you to write clean code and write testable components.
When designing your application structure, the goal is to have loose coupling. Tight coupling occurs when one component knows a lot about another component. This is often caused by a component’s inability to encapsulate its internal structure. If the component’s encapsulation is not correct, it will be hard to test.
Single responsibility principle
Using the Single Responsibility Principle is a great way to write code that’s easier to maintain and test. It’s also a good way to refactor code.
The Single Responsibility Principle states that a class should have only one function or responsibility. This will help you keep your methods and classes smaller and more readable. It will also reduce the risk of introducing unexpected side effects of future changes.
This concept applies to all software components. It helps achieve separation of concerns, which is important when designing and implementing an application. It also makes it easier to explain what your classes do to others. It also improves the speed of development.
Using the latest and greatest in unit testing technologies isn’t the only way to ensure your code is as testable as possible. One of the best ways to boost testability is by minimizing duplication of effort and avoiding hard-coded dependencies. This translates into code that is easier to maintain and less likely to break down.
The simplest and most effective way to do this is by limiting the number of modules your code spans. This is particularly true if your program interacts with other systems such as databases and web services. If you’re able to whittle your code down to just a few, you’ll be rewarded with highly readable and testable code that is easily maintainable.
Object graph construction with application logic
Object graph construction with application logic has been around for quite some time. As you would expect, it’s easier to write testable code when your objects aren’t so tied down to a particular context. In some cases, this can make the task even more challenging.
The best way to do this is by using a dependency injection framework like Guice. This will help ensure that you don’t have to deal with the complexities of configuring and testing your dependencies. In addition to avoiding this common annoyance, it will also reduce the amount of boilerplate code you have to write. In fact, a well implemented DI framework will help you write testable code that is clean, simple, and reusable.
Avoiding dependency injection
Using dependency injection can help you avoid hidden dependencies. It can also help you make your code more flexible and testable. But it’s important to keep in mind that it’s not always the right choice. There are other ways to get the same results.
For instance, you can use a service locator pattern. This works well in a dynamic environment. Objects that want to use dependencies should receive them from a source outside of the class.
You can also make public methods virtual. This helps to encapsulate behavior and reduce the number of references required by the injection assembly. The main downside is that output from the methods may not be predictable.