Autonomous QA Agent: A Retrieval-Augmented Framework for Reliable Selenium Script Generation

• URL: http://arxiv.org/abs/2601.06034v1
• Date: Fri, 28 Nov 2025 10:25:12 GMT
• Title: Autonomous QA Agent: A Retrieval-Augmented Framework for Reliable Selenium Script Generation
• Authors: Dudekula Kasim Vali,
• Abstract summary: Large Language Models (LLMs) can generate code that hallucinates non-existent UI elements.<n>We present the Autonomous QA Agent, a Retrieval-Augmented Generation (RAG) system that grounds script generation in project-specific documentation and HTML structure.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Software testing is critical in the software development lifecycle, yet translating requirements into executable test scripts remains manual and error-prone. While Large Language Models (LLMs) can generate code, they often hallucinate non-existent UI elements. We present the Autonomous QA Agent, a Retrieval-Augmented Generation (RAG) system that grounds Selenium script generation in project-specific documentation and HTML structure. By ingesting diverse formats (Markdown, PDF, HTML) into a vector database, our system retrieves relevant context before generation. Evaluation on 20 e-commerce test scenarios shows our RAG approach achieves 100% (20/20) syntax validity and 90% (18/20, 95% CI: [85%, 95%], p < 0.001) execution success, compared to 30% for standard LLM generation. While our evaluation is limited to a single domain, our method significantly reduces hallucinations by grounding generation in actual DOM structure, demonstrating RAG's potential for automated UI testing.

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