Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs

2023/10/21 by Chetan Arora, John Grundy, Arora, Chetan +3 · 9 citations
Computer Science · #FOS: Computer and information sciences #Software Engineering (cs.SE) #Software Engineering Research #Software Engineering Techniques and Practices #Software Reliability and Analysis Research

paper · pdf · doi:10.48550/arxiv.2310.13976

openalex publication_date 2023/10/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Requirements Engineering (RE) is a critical phase in software development including the elicitation, analysis, specification, and validation of software requirements. Despite the importance of RE, it remains a challenging process due to the complexities of communication, uncertainty in the early stages and inadequate automation support. In recent years, large-language models (LLMs) have shown significant promise in diverse domains, including natural language processing, code generation, and program understanding. This chapter explores the potential of LLMs in driving RE processes, aiming to improve the efficiency and accuracy of requirements-related tasks. We propose key directions and SWOT analysis for research and development in using LLMs for RE, focusing on the potential for requirements elicitation, analysis, specification, and validation. We further present the results from a preliminary evaluation, in this context.

Cited by

• AI for Requirements Engineering: Industry adoption and Practitioner perspectives
• U2F: Encouraging SWE-Agent to Seize Novelty without Losing Feasibility
• Towards Human-AI Synergy in Requirements Engineering: A Framework and Preliminary Study
• TREAT: A Code LLMs Trustworthiness / Reliability Evaluation and Testing Framework
• Reconsidering Requirements Engineering: Human-AI Collaboration in AI-Native Software Development
• From Law to Gherkin: A Human-Centred Quasi-Experiment on the Quality of LLM-Generated Behavioural Specifications from Food-Safety Regulations
• Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs
• Automatic Classification of User Requirements from Online Feedback -- A Replication Study
• Exploring the Use of LLMs for Requirements Specification in an IT Consulting Company

Related

• Prompt Engineering Guidelines for Using Large Language Models in Requirements Engineering
• Large Language Models (LLMs) for Requirements Engineering (RE): A Systematic Literature Review
• Using Large Language Models for Natural Language Processing Tasks in Requirements Engineering: A Systematic Guideline
• Analysis of LLMs vs Human Experts in Requirements Engineering
• ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation