Evaluating Generative AI for HTML Development
Guardado en:
| Publicado en: | Technologies vol. 13, no. 10 (2025), p. 445-465 |
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| Autor principal: | |
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| Publicado: |
MDPI AG
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| Resumen: | The adoption of generative Artificial Intelligence (AI) tools in web development implementation tasks is increasing exponentially. This paper evaluates the performance of five leading Generative AI models: ChatGPT-4.0, DeepSeek-V3, Gemini-1.5, Copilot (March 2025 release), and Claude-3, in building HTML components. This study presents a structured evaluation of AI-generated HTML code produced by leading Generative AI models. We have designed a set of prompts for popular tasks to generate five standardized HTML components: a contact form, a navigation menu, a blog post layout, a product listing page, and a dashboard interface. The responses were evaluated across five dimensions: semantic structure, accessibility, efficiency, readability, and search engine optimization (SEO). Results show that while AI-generated HTML can achieve high validation scores, deficiencies remain in semantic structuring and accessibility, with measurable differences between models. The results show variation in the quality and structure of the generated HTML. These results provide practical insights into the limitations and strengths of the current use of AI tools in HTML development. |
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| ISSN: | 2227-7080 |
| DOI: | 10.3390/technologies13100445 |
| Fuente: | Materials Science Database |