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

Chetan Arora, John Grundy, Mohamed Abdelrazek

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Researchpeer-review

16 Citations (Scopus)

Abstract

Requirements Engineering (RE) is a critical phase in software develop-ment 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.

Original languageEnglish
Title of host publicationGenerative AI for Effective Software Development
EditorsAnh Nguyen-Duc, Pekka Abrahamsson, Foutse Khomh
Place of PublicationCham Switzerland
PublisherSpringer
Chapter6
Pages129-148
Number of pages20
Edition1st
ISBN (Electronic)9783031556425
ISBN (Print)9783031556418
DOIs
Publication statusPublished - 2024

Keywords

  • Generative AI
  • Large language models (LLMs)
  • Natural language processing
  • Requirements engineering
  • Software engineering

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