Five Common Types of Mobile App Bugs Found Using AI
Among all mobile apps, the current error rate is believed to be at 15%. With a thousand new apps launching daily and a constant increase of mobile devices, there’s a need for a scalable solution to create and maintain high-quality apps hassle free. Thanks to Artificial Intelligence (AI), exploratory testing is advancing and proving to detect mobile bugs at scale. In this talk, join Sandy Park as she examines the five most common types of errors found through over 10,000 hours of AI-powered testing with actual samples. She will introduce the challenges of each and explain how the heuristic or rule-based approach was not able to address the issues efficiently. She will cover topics such as broken element identification and Z-order detection for layered views. Finally, Sandy will share deep learning methods such as RCNN and LSTM which enhance the coverage and reliability. Through the session, attendees will leave with a practical checklist of the hidden spot errors that could be prevented and how this framework could be integrated into CI/CD environments.