Harder, better, faster, stronger: depending on your age, these words will probably get Daft Punk or Kanye West stuck in your head. This mantra can apply to web app testing as well: the better and faster your test scripts run, the faster you can fix bugs, release better code, and deliver a stronger web app to make customers happy.
The best way to speed up your automated testing process without sacrificing quality is through parallelization. Parallelization in testing is when multiple automated test scripts run at the same time against various environment configurations, either locally or in your CI/CD pipeline. For visual regression tests, parallelization allows for multiple user interface (UI) tests to run across different device emulators and screen resolutions at the same time.
This article explores the benefits of parallelization and best practices for adding parallelization to your visual testing process.
Parallelization has benefits beyond just increasing the speed of test results—here are some others benefits that you may not be aware of:
With a standard automated testing strategy, each test script runs sequentially, one at a time, in each environment configuration. It’s easy to do the math and see how much time that would take, especially when your tests are part of your CI/CD pipeline and run multiple times per day.
With parallel testing, the time it takes to run a single parallel test suite is equivalent to the length of your longest test. For example, if you have five tests that are each two minutes long, then your parallel testing suite will take two minutes to run. If you were to run these five tests sequentially, your tests would take 10 minutes to run from start to finish. The less time it takes to run tests, the more tests you can run more frequently.
Saving time on running tests also allows you to expand your testing coverage by running your scripts against more environment configurations. This is especially important for visual testing where you need to make sure your app looks and functions as designed across all operating systems, screen sizes, and screen resolutions.
Increased speed, frequency, and coverage mean you get better, more consistent test results and a stronger overall automated testing strategy. It’s that simple.
Doing some work upfront helps make sure your tests are optimized for parallel testing so that your tests run smoothly and efficiently every time. Here are some best practices for optimizing your parallel testing process.
For most software development teams, standing up and maintaining your own testing infrastructure would be inefficient and costly. For parallel testing, it’s optimal to use a cloud-based solution like Sauce Labs to ensure you have reliable access to the full scope of environment configurations and test coverage you need.
At Sauce Labs, we’ve found that the three key ingredients to effective parallel tests are atomic, autonomous, and short:
Atomic: each test should test for only one thing.
Autonomous: any test can run in isolation at the same time or in any order with another test.
Short: each test should be of a similar length (ideally under two minutes).
Another key to improving test parallelization is to make sure your tests can run independently of one another. In other words, each test script should manage its own data. For example, if you have a test script that assumes a certain user exists in the database, this user may not exist when the test is run in a parallel state. But if the test script starts by configuring the data it needs to run successfully--in this example, by creating the desired user in the database--it can run independently of other tests. Here are some data management approaches you can use to remove data dependencies from your parallel tests.
Parallelization is your most powerful tool for speeding up automated visual testing without degrading the quality of your tests or your app. In fact, when deployed thoughtfully and effectively, parallelization can return better, more consistent results and enhance the overall health of your CI/CD pipeline.