报告详情
ReqGenAI: A Multi-Agent AI Framework for Automated Requirement Engineering with Conflict Detection
编号：163
访问权限：仅限参会人
更新：2026-11-10 17:00:01 浏览：9次
Online
报告开始：2026年11月20日 16:45（Asia/Kolkata）
报告时间：15min
所在会场：[S4] Artificial Intelligence and Intelligent Computing [S4-4] Artificial Intelligence and Intelligent Computing
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摘要
Requirement engineering is a critical phase of the Software Development Life Cycle (SDLC), where incomplete, ambiguous, or inconsistent requirements often lead to project delays, increased costs, and software failures. Existing requirement analysis and documentation processes are predominantly manual, making them time-consuming and prone to human error. This paper proposes an AI-powered Requirement Engineering System that automates the transformation of unstructured client requirements into structured software documentation. The proposed framework employs a Multi-Agent AI architecture in which specialized agents collaboratively perform requirement extraction, functional and non-functional requirement classification, Agile user story generation, database entity identification, consistency and ambiguity analysis, and Software Requirement Specification (SRS) generation. To improve the reliability and domain relevance of generated outputs, the system integrates Retrieval-Augmented Generation (RAG) with SRS templates and established requirement engineering standards, enabling context-aware and standards-compliant documentation. The key novelty of this work lies in its hybrid conflict detection mechanism, which combines rule-based heuristics with embedding-based semantic similarity (BGE/SBERT) and LLM-driven reasoning, achieving a level of consistency analysis that neither purely rule-based nor purely generative approaches can accomplish alone. The automated consistency analysis further identifies conflicting, incomplete, and ambiguous requirements during the early stages of software development, reducing the likelihood of costly downstream defects. The proposed framework significantly minimizes documentation effort, improves requirement quality, and accelerates project planning for students, software practitioners, startups, and development teams. By combining generative AI, multi-agent collaboration, and knowledge retrieval, the system provides an intelligent and scalable solution for modern requirement engineering and software documentation.
关键词
Requirement Engineering, Multi-Agent AI, Retrieval-Augmented Generation (RAG), Software Requirement Specification (SRS), Natural Language Processing, Consistency Analysis, Generative AI.
报告人
Ishwariya M P
Student Velammal College of Engineering and Technonology Ragshi M G A
Student Velammal College of Engineering and Technology稿件作者
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重要日期
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会议日期
11月20日
2026
至11月22日
2026
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10月31日 2026
初稿截稿日期
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11月07日 2026
提前注册日期
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11月22日 2026
注册截止日期
主办单位
United Societies of Science
承办单位
Pondicherry University
协办单位
IEEE Section
IEEE Madras Section
IEEE Madras Section
联系方式
- ICon INDIA 2026
- ic******@usssociety.org
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