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Accessibility Testing is a software testing technique that checks if a website or app is easily usable by every user on the internet, including individuals with disabilities or special needs. Often considered a sub-category of usability testing, it ensures that specific, unchangeable conditions do not prevent a person from accessing online resources as easily as anyone else.
Accessibility testing is significant and should be included in testing pipelines for two significant reasons:
Every year, pundits and critics offer their predictions for the year ahead. Here are my predictions for test automation in 2021. (Note: these are my personal predictions)
Teams running Continuous Integration/Continuous Deployment (CICD) have learned that developers must own the quality of their code. In 2021, everyone else will figure that out, too. Engineers know that the delay between developing code and finding bugs produces inefficient development teams. Companies running standalone QA teams find bugs later than teams with integrated quality. In 2021, this difference will begin to become painful as more companies adopt quality engineering in the midst of development.
In an era of digital transformation, software is no longer just a tool; it is at the heart of every business. Why is it at the heart of a business? Because we are constantly interacting with our users and customers through a booming number of software applications: web, mobile, and native.
Applitools recently sponsored an independent survey with 400 engineering and quality assurance leaders from a variety of Fortune 500 companies. Among other things, they were asked how many different applications they used in their organization and how many pages each application included. Let's look at the findings of the survey.
How does functional testing with visual assertions help simplify test development for complex real-world apps? Like, say, a retail app with inventory, product details, rotating displays, and shopping carts?
My special blog series discusses Modern Functional Testing with Visual AI, Raja Rao’s course on Test Automation University. I arrived at Chapter 6 – E-Commerce Real World Example. In this review, I hope to give you an overview of Raja’s examples and how they might apply to your test challenges.
When you have multiple variations of your app, how do you automate the process to validate each variation?
A/B testing is a technique used to compare multiple experimental variations of the same application to determine which one is more effective with users. You typically run A/B tests to get statistically valid measures of effectiveness. But, do you know why one version is better than the other? It could be that one contains a defect.
Let's be honest: if you're using legacy test approaches, you spend a ton of time maintaining your data-driven tests. And that time slows you down when you're trying to keep up with a dev team that thinks, "We're coding to standards — it should all run everywhere."
Think about the most difficult parts of coding and maintaining your test infrastructure. The simplest part involves writing the initial tests. You use what you see and your understanding of expected behavior to drive the tests. Test maintenance costs can drive you crazy.
If you don’t know what visual testing is, or you’ve heard of it but aren’t sure how it’s different from your existing test efforts, this post is for you.
You may also enjoy: Visual Testing [RefCard]
Read on to learn about the differences (and overlap) between functional and visual testing, and the benefits and challenges that come with visual testing.