Problem
Research questions and friction points this paper is trying to address.
configurator usability
user interface analysis
usability heuristics
multimodal large language models
software configuration
Usability Analysis of Configurator User Interfaces with Multimodal Large Language Models
🤖 AI Summary
This study addresses the lack of domain-specific usability evaluation guidelines and systematic analytical tools for configurator user interfaces, which has led to inefficient and insufficiently expert assessments. To bridge this gap, the work proposes a semi-automated evaluation framework that leverages multimodal large language models (MLLMs) to jointly reason over visual and textual inputs. Grounded in 18 configurator-specific usability criteria, the framework automatically identifies usability issues, rates their severity, and generates actionable improvement suggestions. Experimental validation on 16 real-world configurators demonstrates that the approach reliably and efficiently diagnoses configurator-unique usability problems, substantially reducing manual effort while exhibiting strong scalability and adaptability across domains.
📝 Abstract
Configuration is a key technology for tailoring complex software systems, services, and products. A successful application of configurators not only depends on technical correctness, performance, and domain modeling but also on their usability. While general usability heuristics are widely used, configurator-specific criteria and tool support for systematic user interface (UI) analysis are limited. This paper explores the use of multimodal large language models (MLLMs) for scalable and semi-automated usability analysis of configurator UIs. We synthesize 18 configurator-specific usability criteria from the literature and apply these criteria in an MLLM-based analysis of 16 real-world configurators. Each criterion is assessed individually to generate severity ratings for usability issues and actionable improvement suggestions. A review of the results confirms that MLLMs can reliably identify configurator-specific usability issues and provide domain-aware improvement recommendations. Although human validation remains necessary, this approach has the potential to significantly reduce the required effort to analyze configurator usability.
Innovation
Methods, ideas, or system contributions that make the work stand out.
multimodal large language models
configurator usability
user interface analysis
domain-specific heuristics
semi-automated evaluation
🔎 Similar Papers
No similar papers found.
💼 Related Jobs
