Although software testing is key to a safe society, the process itself is often perceived as a stressful and boring chore. The adverse effect is a suboptimal testing that might leave wicked dangerous, bugs undetected. A better understanding of what testers “feel” can remedy this situation.
The question is how to measure what testers feel? Students who worked with DBugIT/BugZoo, an innovative tool developed at the VU for teaching software testing, reported feelings such as boredom and stress for not finding bugs, excitement when finding a bug, and a drive to continue testing to find more.
This project will use AI and various physiological wearable sensors (with a focus on measuring cardiac activity and skin conductance) to recognize in real-time the emotions of testers at work. Based on the inferred emotion, an adaptive bio-feedback will emerge, to encourage testers to continue their work in optimal conditions. Although AI-enabled emotion recognition is not new, applying it in the particular field of software testing teaching is to our knowledge, innovative. When successful, this challenging project will contribute to a more inspiring and motivating environment for testers in academia and IT industry, and eventually to high-quality software we all can rely on.