Achieving web accessibility is essential to building inclusive digital experiences. However, accessibility issues are often identified only after a website has been fully developed, making them difficult to address. This paper introduces a Visual Studio Code plugin that integrates calls to a Large Language Model (LLM) to assist developers in identifying and resolving accessibility issues within the IDE, reducing accessibility defects that might otherwise reach the production environment. Our evaluation shows promising results: the plugin effectively generates functioning fixes for accessibility issues when the errors are correctly detected. However, detecting errors using a generic prompt - designed for broad applicability across various code structures - remains challenging and limited in accuracy.

A Prototype VS Code Extension to Improve Web Accessible Development / Calì, Elisa; Fulcini, Tommaso; Coppola, Riccardo; Laudadio, Lorenzo; Torchiano, Marco. - ELETTRONICO. - (2025), pp. 52-57. (Intervento presentato al convegno 2nd Workshop on Integrated Development Environments tenutosi a Ottawa (CAN) nel 27 Aprile - 3 Maggio 2025) [10.1109/IDE66625.2025.00015].

A Prototype VS Code Extension to Improve Web Accessible Development

Tommaso Fulcini;Riccardo Coppola;Lorenzo Laudadio;Marco Torchiano
2025

Abstract

Achieving web accessibility is essential to building inclusive digital experiences. However, accessibility issues are often identified only after a website has been fully developed, making them difficult to address. This paper introduces a Visual Studio Code plugin that integrates calls to a Large Language Model (LLM) to assist developers in identifying and resolving accessibility issues within the IDE, reducing accessibility defects that might otherwise reach the production environment. Our evaluation shows promising results: the plugin effectively generates functioning fixes for accessibility issues when the errors are correctly detected. However, detecting errors using a generic prompt - designed for broad applicability across various code structures - remains challenging and limited in accuracy.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2996559