Detecting UX smells in Visual Studio Code using LLMs
Andr\'es Rodriguez, Juan Cruz Gardey, Alejandra Garrido
TL;DR
This paper introduces an LLM-assisted method to identify UX issues in Visual Studio Code by analyzing GitHub issues, revealing key areas like informativeness and clarity that impact developer experience.
Contribution
The study presents a novel approach combining LLMs and expert review to systematically detect and classify UX smells in a popular IDE.
Findings
UX smells mainly affect informativeness, clarity, intuitiveness, and efficiency
Majority of UX issues are concentrated in these key qualities
The approach effectively identifies recurring UX problems
Abstract
Integrated Development Environments shape developers' daily experience, yet the empirical study of their usability and user experience (UX) remains limited. This work presents an LLM-assisted approach to detecting UX smells in Visual Studio Code by mining and classifying user-reported issues from the GitHub repository. Using a validated taxonomy and expert review, we identified recurring UX problems that affect the developer experience. Our results show that the majority of UX smells are concentrated in informativeness, clarity, intuitiveness, and efficiency, qualities that developers value most.
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Taxonomy
TopicsSoftware Engineering Research · Software Engineering Techniques and Practices · Open Source Software Innovations