Author: Kevin Surace

In a shocking display of incompetence, millions of computers around the world simultaneously became unusable, all thanks to a bug that led to the dreaded “Blue Screen of Death.” CrowdStrike, a US cybersecurity company based in Texas, offers ransomware, malware, and internet security products primarily to businesses and large organizations. But on Friday, July 19,

As technology advances at an exponential rate, the role of artificial intelligence (AI) in software quality assurance (SQA) has become increasingly prominent. From automating mundane tasks to enhancing overall efficiency and productivity, AI has proven itself as a powerful tool in the arsenal of QA teams. But what does the future hold? Can AI go

Software QA is undergoing a sea change due to generative AI-driven testing. Given that, this post compares and contrasts generative AI (GenAI) test creation with traditional scripting methods.  It does so across half-a-dozen aspects of scripting, including the development process, efficiency, accuracy, customization and adaptability, maintainability, and ongoing improvement. 6 Points of Comparison 1. Development

Software QA is undergoing a sea change due to generative AI-driven testing. That begs the question of how to practice responsible AI in software testing. Hence, this post provides eleven considerations for responsible testing when using generative AI (GenAI). First, let’s note that responsible AI is an emerging area of AI governance covering ethics, morals

Digital transformation is happening. In many cases QA isn’t involved, but they should be.  No one can undergo a digital transformation in any corporation without improving their quality by 10x, literally. This means improving visibility by 10x, and being able to raise that visibility all the way to the CIO or CTO. And you need

There are different approaches to low code / no code for. The first generation of low code/no code would record what you did and what you said on a web application then write some kind of script for you. However, you could not edit that script, as it was truly no code. It right, it

Artificial intelligence (AI) is a technology that’s transforming quality in software testing and revolutionizing other walks of life. It has been improving the quality of our lives for over a decade, and Appvance has been at the forefront of the technology since its inception. There were a few inklings of it when Facebook started to

Using artificial intelligence (AI) in testing to visually expand the accessor pool increases accuracy, productivity, and almost completely eliminates maintenance. The number one reason test cases get re-written is that an accessor has changed.  Using AI and image recognition provides more ways to recognize that accessor, which improves the stability and reliability of the test.

For the better part of 20 years, the e-commerce QA test industry has known that every one-second delay in response, they can lose up to half the page audience. Not because the user bought somewhere else, but because they became distracted. Today’s distractions are probably much higher than they were when those original studies were

Generative AI is a type of artificial intelligence (AI), one of many, where it is trained on a very large set of data. After training, if you give it some direction, it generates something for you. It can generate an answer, text, a picture, or it might generate code. It generates things based on your