Agents for Automated User Experience Testing

TL;DR

This paper proposes an agent-based approach with affective computing to automate user experience testing, aiming to overcome the slow and resource-intensive nature of traditional user testing methods.

Contribution

It introduces a novel agent framework with problem solving and affect modeling capabilities for automated UX testing, a new direction in the field.

Findings

Agents can simulate affective states during UX testing

Preliminary results support the feasibility of affective agents in UX evaluation

The approach shows promise for reducing testing time and resources

Abstract

The automation of functional testing in software has allowed developers to continuously check for negative impacts on functionality throughout the iterative phases of development. This is not the case for User eXperience (UX), which has hitherto relied almost exclusively on testing with real users. User testing is a slow endeavour that can become a bottleneck for development of interactive systems. To address this problem, we here propose an agent based approach for automatic UX testing. We develop agents with basic problem solving skills and a core affect model, allowing us to model an artificial affective state as they traverse different levels of a game. Although this research is still at a primordial state, we believe the results here presented make a strong case for the use of intelligent agents endowed with affective computing models for automating UX testing.