Making Time for Bigger Bugs - Leveraging AI to Strengthen Your Automated Tests
Test automation rarely lives up to its promise: Handling rote testing tasks, while freeing QA to dig in and find the big, complicated, dangerous bugs. It fails because traditional test automation is inherently flaky, requiring constant maintenance to remain operational and reliable. We start automation hoping to simplify, then find that for every hour we write test code, we either spend 5-10 hours maintaining it or give up and watch it die. Instead of hunting the big bugs, we’re trawling logs to figure out what broke this time. Why? Because traditional test automation is tied tightly to application code! Join Seth Stradling as he discusses how to decouple test automation code from the application under test using computer vision and AI. Learn how a software development kit that splices cloud-based ML into custom selenium and appium element identification strategies, can allow you to quickly and easily integrate AI directly into test scripts. Seth will round up the session by looking at implementation approaches and future plans for expanding access to this technology, which makes it easier to spend time hunting bugs instead of maintaining code.
Seth Stradling
Seth Stradling is a SDET and current Solutions Engineer at test.ai, an AI-driven vision-first test automation platform. For Seth, everything in the last 12 years has been QA - SaaS development, test automation, security review process management, or logistics security and capabilities assessment - whether or not he knew it at the time. Before test.ai, Seth worked at Domo, a SaaS business analytics platform, and Los Alamos National Laboratory. Seth loves watermelon, and firmly believes that most birds are real.