
Visual Validation with Dynamic Data
You’re running functional tests with visual validation, and you have dynamic data. Dynamic data looks different every time you inspect it. How do you do functional testing with visual validation,…
You’re running functional tests with visual validation, and you have dynamic data. Dynamic data looks different every time you inspect it. How do you do functional testing with visual validation,…
While Cypress.io lacks support for cross-browser testing, Applitools supports it via their Applitools Ultrafast Grid. You can combine the best of both worlds by using Cypress.io to write your integration and E2E tests and letting Applitools Ultrafast Grid handle cross-browser testing for you.
Visual AI simplifies your functional test while adding visual coverage. Visual AI compares rendered output against rendered output. If visual differences exist, you can identify those as intended or not.
As you know, I’m taking Raja Rao’s Test Automation University Course, Modern Functional Test Automation through Visual AI. Today we’ll discuss testing iFrames. In Chapter 5, Raja refers to iFrames as…
With today’s standards, developers can develop once, test in development, and assume they are done. Legacy QA productivity remains limited because QA must still run tests one device, operating system, browser, and viewport size at a time. All the tools that provide test scaling still require validation one-at-a-time, either because tools ignore rendering or flag too many erroneous visual differences. Until Applitools introduced Visual AI testing with Ultrafast Grid.
Imagine this. You built a page with CanvasJS, and you want to test the graphs. How do you create an automated test for the graphical representations? It’s testing dynamic content,…
Many teams don’t automate tests to validate multiple variations because it’s “throw away” code. You’re not entirely sure which variation you’ll get each time the test runs. If you did write test automation, you may need a bunch of conditional logic in your test code to handle both variations. What if instead of writing and maintaining all of this code, you used visual testing instead? Would that make things easier?
Data-driven testing helps build and scale test automation – until you have to maintain your tests. Visual AI helps you test without growing your test code.
If developer-check-in-to-prod works for your organization, then you should do it…provided you understand the risk. This risk manifests in two big buckets: cost of change and cost of failure.
The key to becoming a Test Automation Rockstar is to learn how to use Applitools. And we have 40,000 reasons as an incentive for you to learn Applitools now.
How Cross-Browser Testing is evolving
The first chapter compares modern functional testing with Visual AI against legacy functional testing with coded assertions of application output. Raja states that Visual AI allows for modern functional testing while using an existing functional test tool that relies on coded assertions results in lost productivity.