Evaluating Generative AI for HTML Development

-д хадгалсан:

Номзүйн дэлгэрэнгүй
-д хэвлэсэн:	Technologies vol. 13, no. 10 (2025), p. 445-465
Үндсэн зохиолч:	Alahmad, Ahmad Salah
Бусад зохиолчид:	Hasan, Kahtan
Хэвлэсэн:	MDPI AG
Нөхцлүүд:	Hangzhou DeepSeek Artificial Intelligence Co Ltd Standards Software quality Accessibility Programming languages Accuracy Semantics Usability Software development Performance evaluation Chatbots Search engine optimization Generative artificial intelligence Compliance Search engines Large language models HyperText Markup Language Bias
Онлайн хандалт:	Citation/Abstract Full Text + Graphics Full Text - PDF
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!

Тодорхойлолт
Хураангуй:	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.
ISSN:	2227-7080
DOI:	10.3390/technologies13100445
Эх сурвалж:	Materials Science Database