AI-driven testing changes everything for testing teams. These Best Practices ensure best outcomes. I’ve recently published a series of posts on Best Practices for different aspects of software QA in the age of AI-driven testing. This post serves as a portal to them. Before listing the posts, it’s worth noting that everything has changed in
AI-enabled software testing changes the game for testing teams and their leaders. Here are four best practices and an important tip for making the most of this unprecedentedly powerful automation technology. Best Practice #1: Segment test cases for human or AI creation. Identify the critical test cases that humans should write. Have test engineers write
Introduction Software test automation has been a cornerstone of software quality for decades. However, the traditional approach to test automation and maintenance has been plagued by high costs, limited resources, and the need to prioritize critical test cases. In recent years, Artificial Intelligence (AI) and especially generative AI has emerged as a game-changer in the
The benefits of AI-driven testing go well beyond automatic test-script generation, profound and game-changing as that is. However, auto test-script generation is robustly covered elsewhere on this blog, so this post introduces two downstream benefits of AI-driven testing: Intelligent Test Prioritization and Test Results Analysis. AI-aided test prioritization and results analysis are each transformative in
The Quantum Leap that AI Can Provide to Testing The buzz around ChatGPT and GPT4, the latest release of the large language model from Open AI, has not abated since it burst onto the tech scene several months ago. Many dev and testing teams are experimenting with leveraging the model to automatically write test scripts.
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
With the growth and evolution of software, the need for effective testing has grown exponentially. Testing today’s applications requires an immense number of complex tasks, as well as a comprehensive understanding of the application’s architecture and functionality. A successful test team must have strong organizational skills to coordinate their efforts and time to ensure that
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