CAST 2022

AI/ML for testing often get a bad reputation because of overstated claims and marketing. However, it is important for software testers to get hands-on exposure to what these technology are, how they work, how they're used for testing, and the challenges with testing AI/ML based systems.

Industry practitioners, vendors and researchers are leveraging AI and machine learning (ML) to develop a new wave of test automation tools. These tools automatically explore, model, reason, learn, and test software applications. With all of the hype and marketing around AI/ML, it can be difficult to determine what this technology is really all about. What are the benefits and limitations of using AI/ML for testing? How do I get started? What tools are available? Are there additional skills I need to learn? In this workshop, you'll get hands-on with AI for software testing by training your first neural network, and developing a testing strategy that seeks to break the teachable machine. You'll play around with computer vision technologies and learn how these advances are being applied to testing problems. Lastly, you'll then take turns putting on your data scientist, ml engineering, and software testing hats to gain practical experience and insights into how AI/ML systems are trained, validated, and evaluated using ML libraries such as Tensorflow, Scikit-Learn, Pandas, and more.