An introduction to frontend testing
Testing frontend code is still a confusing practice to many developers. We break down your different testing options and explains what situations they are best used for.
Frontend testing is a blanket term that covers a variety of automated testing strategies. Some of these, like unit and integration testing, have been an accepted best practice within the backend development community for years. Other strategies are newer, and stem from the changes in what backend and frontend development are used for now.
While your particular application may not need to take advantage of every type of testing that exists, it’s important to know the options that are out there, what they are used for, and when it’s appropriate to use each one. By the end of this article, you should feel comfortable assessing which testing strategies fit best with your team and codebases. The following code examples will be written using the Jasmine framework, but the rules and processes are similar across most testing frameworks.
Unit testing, one of the testing veterans, is at the lowest level of all testing types. Its purpose is to ensure the smallest bits of your code (called units) function independently as expected.
Imagine you have a Lego set for a house. Before you start building, you want to make sure each individual piece is accounted for (five red squares, three yellow rectangles). Unit testing is making sure individual sets of code – things like input validations and calculations – are working as intended before building the larger feature.
It helps to think about unit tests in tandem with the ‘do one thing well’ mantra. If you have a piece of code with a single responsibility, you likely want to write a unit test for it.
Let’s look at the following code snippet, in which we are writing a unit test for a simple calculator:
In our Calculator application, we want to ensure that the calculations always function independently the way we expect. In the example, we want to make sure that we can always accurately add two numbers together.
The first thing we do is describe the series of tests we’re going to run by using Jasmine’s describe. This creates a test suite – a grouping of tests related to a particular area of the application. For our calculator, we will group each calculation test in its own suite.
Suites are great not only for code organisation, but because they enable you to to run suites on their own. If you’re working on a new feature for an application, you don’t want to run every test during active development, as that would be very time consuming. Testing suites individually lets you develop more quickly.
Next, we write our actual tests. Using the it function, we write the feature or piece of functionality we are testing. Our example tests out the addition function, so we will run scenarios that confirm that it’s working correctly.
We then write our test assertion, which is where we test if our code functions as we expect. We initialise our calculator, and run our addNumbers function with the two numbers we wish to add. We store the number as the result , and then assert this is equal to the number we expect (in our case, 10).
If addNumbers fails to return the correct figures, our test will fail. We would write similar tests for our other calculations – subtraction, multiplication, and so on.
If unit tests are like checking each Lego piece, acceptance tests are checking if each stage of building can be completed. Just because all the pieces are accounted for doesn’t mean that the instructions are properly executable and will allow you to build the final model.
Acceptance tests go through your running application and ensure designated actions, user inputs and user flows are completable and functioning. Just because our application’s addNumbers function returns the right number doesn’t mean the calculator interface will definitely function as expected to give the right result. What if our buttons are disabled, or the calculation result doesn’t get displayed? Acceptance tests help us answer these questions.
The structure looks very similar to our unit test: we define a suite with describe, then write our test within the it function, then execute some code and check its outcome. Rather than testing around specific functions and values, however, here we’re testing to see if a particular workflow (a sign-up flow) behaves as expected when we fill in some bad information. There are more minute actions happening here, such as form validations that may be unit tested, as well as any handling for what shows our error state, demonstrated by an element with the ID signupError.
Acceptance tests are a great way to make sure key experience flows are always working correctly. It’s also easy to add tests around edge cases, and help your QA teams find them in your application.
When considering what to write acceptance tests for, your user stories are a great place to start. How does your user interact with your website, and what is the expected outcome of that interaction? It’s different to unit testing, which is better matched to something like function requirements, such as the requirements around a validated field.
Visual regression tests
As mentioned in the introduction, some types of testing are unique to the frontend world. The first of these is visual regression testing. This doesn’t test your code, but rather compares the rendered result of your code – your interface – with the rendered version of your application in production, staging, or a pre-changed local environment. This is typically done by comparing screenshots taken within a headless browser (a browser that runs on the server). Image comparison tools then detect any differences between the two shots.
Using a tool such as PhantomCSS, your tests specify where the test runner should navigate to, take a screenshot, and the framework shows you differences that came up in those views.
Unlike acceptance and unit testing, visual regression testing is hard to benefit from if you’re building something new. As your UI will see rapid and drastic changes throughout the course of active development, you’ll likely save these tests for when pieces of the interface are visually complete. Therefore, visual regression tests are the last tests you should be writing.
Currently, many visual regression tools require a bit of manual effort. You may have to run your screenshot capture before you start development on your branch, or manually update baseline screenshots as you make changes to the interface.
This is simply because of the nature of development – changes to the UI may be intentional, but tests only know ‘yes, this is the same’ or ‘no, this is different’. However, if visual regressions are a pain point within your application, this approach may save your team time and effort overall, compared to constantly fixing regressions.
Accessibility and performance tests
As the culture and awareness around frontend testing grows, so does our ability to test various aspects of the ecosystem. Given the increased focus on accessibility and performance in our technical culture, integrating this into your testing suite helps ensure these concepts remain a priority. If you’re having issues enforcing performance budgets or accessibility standards, this is a way to keep these requirements in the forefront of people’s minds.
Both of these checks can either be integrated into your workflow with build tools like Grunt and Gulp, or semi-manually within your terminal. For performance budgets, a tool like grunt- perfbudget gives you the ability to run your site through WebPageTest automatically within a specified task. However, if you’re not using a task runner, you can also grab perfbudget as a standalone NPM module and run the tests manually.
Here’s what it looks like to run this through the terminal:
The same options are available for accessibility testing. So for Pa11y, you can either run the pa11y command in your browser for output or set up a task to automate this step. In the terminal:
Most tools in these categories are fairly plug-and-play, but also give you the option to customise how the tests get run – for example, you may set them to ignore certain WCAG standards.
Embracing and enforcing a testing culture
Many developers are on board with having some kind of testing present in their codebase, but some are still skeptical about the cost-benefit balance. If you are just considering how testing would fit into your team and workflow, you should think about the following:
Start with known pain points
If you’re constantly seeing the same bugs popping up in certain parts of your codebase, it’s wise to investigate if testing could help. If it’s code regression and it’s not possible to unit-test the code, try to adjust your acceptance tests so they cover the scenario at a higher level. This will also give you a baseline test to experiment against – if the number of regressions on this feature goes down after writing tests, you may find other developers more inclined to embrace testing in the future.
Make it part of the workflow
In order to keep the team honest about their test-writing, everyone should hold themselves and others accountable. Perhaps talking about tests becomes part of your code review process: ask why tests weren’t written, or point out areas where they might be helpful. By having an open dialogue about tests, you may find ways to motivate your team to keep writing them. Using a continuous integration service like Travis CI to run your test suite automatically on your development branches can also make your test suite more visible.
Don’t do everything at once
For teams that are new to testing, adopting all the testing types at once might be overwhelming – and if you’re starting with new code, you might not even need all the methods. For example, if you don’t have a lot of client-side logic or user interaction, maybe visual regression tests will cover most of your application. Introducing one testing type at a time will give your team a chance to learn how to test and adjust any parts of the process that prove difficult. At the end of the day, your team needs to be on board and dedicated to this practice.
Revisit and review
Testing, like any other part of your codebase, requires constant revisits to make sure your current implementation still makes sense. Remember, a test suite nobody runs is a test suite that may as well not exist. But if you put the time and effort into your testing strategy, the time saved by fixing regressions means time that can spent building new features, or making your existing code even better.