Research

Paper

AI LLM February 25, 2026

Detecting UX smells in Visual Studio Code using LLMs

Authors

Andrés Rodriguez, Juan Cruz Gardey, Alejandra Garrido

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.

Metadata

arXiv ID: 2602.22020
Provider: ARXIV
Primary Category: cs.SE
Published: 2026-02-25
Fetched: 2026-02-26 05:00

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Raw Data (Debug)
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