When writing your test automation scripts, it can be especially difficult to write code that adequately identifies visual defects. Typical functional tests do a poor job capturing all visual changes and they also leave you with lengthy and flaky code. And when your code becomes flaky, it becomes unreliable

The Problem with Flaky Tests

Your website or application will eventually go through multiple iterations, and your visual tests will constantly evolve. As they do, you will write longer and more complex scripts. And the more complex your script becomes, the greater the chance it can fail randomly – meaning your test is brittle or flaky.

Flaky tests pose several problems for your organization:

1. They cost you money – Longer code requires more time and resources to debug.
2. They slow down your delivery – Flaky tests are unpredictable and take time out of your schedule to debug, hindering your ability to progress on other work.
3. Knowledge becomes scarce – Developers are constantly pulled in multiple directions, and complex code can leave you reliant on a few resident experts for their knowledge. This creates information and development bottlenecks.
4. They impact your test quality – Flaky tests are non-deterministic and leave you with more manual work to investigate. Additionally, this fosters poor QA coding practices.
5. You can accidentally ship faulty commits – How often have you simply “run the test again” because you know it might pass on a subsequent run? This can leave you ignoring what may be a bug and merge it into production.

VisualTest Simplifies Your Code with AI

Visual defects are challenging to evaluate in an automated test so it’s important to consider how you can use AI when establishing your testing methodology.

Say a business-critical GUI component starts rendering poorly; a typical functional test will ineffectively catch and verify that element’s visual fidelity. Users might try to do something like this: find web attributes and start chaining assertions against those values.

Not only does this make your code long, but it makes it inconsistent. Even slight visual changes can cause your code to fail leaving you with more manual work correcting it. What good is test automation that requires constant manual intervention?

VisualTest solves this problem by removing the need for writing lengthy assertions. VisualTest uses AI to replicate the human eye and evaluate all the visual elements of your UI with a single line of code. See an example here:

You can evaluate individual elements or entire webpages without needing to write hundreds of lines of code, saving your tests from becoming flaky.

Running reliable and comprehensive UI tests are key for giving your users an error-free user experience. For more information and a demo, check out our on-demand webinar on how to Simplify Your Code using VisualTest, and start a free trial today!