Discover how Ahmed, a seasoned software QA/Test engineer, is transforming visual regression testing using multi-modal generative AI. This session introduces an innovative approach that streamlines data validation and enhances design change detection through AI-powered analysis of web pages and UI components. 
Experience a live demo showcasing the practical application of this cutting-edge technology and learn how AI can automate and improve test case generation, ensuring your UI remains consistent and accurate. 
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Hi there,
If you couldn’t catch the session live, don’t worry! You can watch the recording here:
Additionally, we’ve got you covered with a detailed session blog:
Here are some of the Q&As from this session:
How can we integrate this with legacy systems?
Ahmed Khalifa: When working with legacy systems, it’s crucial to approach integration thoughtfully. Rather than trying to integrate everything at once, start small and choose specific areas where new technologies can be effectively applied. In my projects, for instance, we have various quality engineering capabilities, including test analysis, automation, design, and strategy. We explore how generative AI can enhance these areas, starting with small, manageable tasks to assess improvements.
It’s also important to remember that the effectiveness of generative AI heavily depends on the quality of the input data. If the input from a legacy system is incomplete or lacks necessary information, the output may not meet expectations.
How do you ensure the accuracy & reliability of test cases generated by multi-modal generative AI?
Ahmed Khalifa: It’s crucial to have a human in the loop when using generative AI. While these systems can be incredibly helpful, you shouldn’t rely entirely on their outputs. It’s important to assess and verify the results yourself. Generative AI can provide a strong starting point and save you time, but ensuring reliability and accuracy still requires human oversight.
Can visual AI handle and test dynamic elements like Videos Ads, Picture Ads, etc. in a webpage?
Ahmed Khalifa: I haven’t used it for every daily task, but I did test its capabilities to showcase trends. What I found was that it effectively managed tasks such as handling pop-ups or entering codes to bypass screens. It worked well out of the box.
Additionally, I used it for video analysis, and it performed exceptionally. The system could slice videos into frames and accurately understand their content. Overall, it appears to be capable of handling various tasks involving video and image analysis effectively.
How can organizations validate the reliability of AI-generated visual test cases and ensure they reflect realistic user experiences?
Can you share any real-world examples of how multi-modal AI has enhanced visual regression testing?
What challenges did you face in implementing multi-modal generative AI for visual regression testing & how did you overcome them?
is it same as experience based testing when comes to functional aspects of testing? or Review based testing
Does this mean we can use Visual regression for web based front end testing - Appearance, color, etc and Dashboard testing?
Can we integrate design tools like Figma as the visual input - to test live output such as webpages?
Can this be used to test mobile apps on all platforms?
