Does GenAI Make Usability Testing Obsolete?
Ali Ebrahimi Pourasad, Walid Maalej

TL;DR
This paper introduces UX-LLM, a Large Vision-Language Model tool that predicts usability issues in iOS apps, offering a supplementary approach to traditional usability testing, especially beneficial for small teams with limited resources.
Contribution
The paper presents UX-LLM, a novel vision-language model-based tool for predicting usability issues, evaluated against traditional methods, highlighting its strengths and limitations.
Findings
UX-LLM achieved precision of 0.61-0.66 and recall of 0.35-0.38.
UX-LLM identified unknown usability issues in a real app.
Developers found UX-LLM useful but with integration concerns.
Abstract
Ensuring usability is crucial for the success of mobile apps. Usability issues can compromise user experience and negatively impact the perceived app quality. This paper presents UX-LLM, a novel tool powered by a Large Vision-Language Model that predicts usability issues in iOS apps. To evaluate the performance of UX-LLM, we predicted usability issues in two open-source apps of a medium complexity and asked two usability experts to assess the predictions. We also performed traditional usability testing and expert review for both apps and compared the results to those of UX-LLM. UX-LLM demonstrated precision ranging from 0.61 and 0.66 and recall between 0.35 and 0.38, indicating its ability to identify valid usability issues, yet failing to capture the majority of issues. Finally, we conducted a focus group with an app development team of a capstone project developing a transit app for…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsUsability and User Interface Design
