The Role of Generative AI Models in Requirements Engineering: A Systematic Literature Review

被引:0
作者
Vasudevan, Poonkuzhali [1 ]
Reddivari, Sandeep [1 ]
机构
[1] Univ North Florida, Jacksonville, FL 32224 USA
来源
PROCEEDINGS OF THE 2025 ACM SOUTHEAST CONFERENCE, ACMSE 2025 | 2025年
关键词
Requirements Engineering; Generative AI; Large Language Models;
D O I
10.1145/3696673.3723053
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The software engineering field is experiencing rapid growth, driven by recent advancements in Artificial Intelligence (AI), particularly in Generative AI (GenAI) and Large Language Models (LLMs). Requirements Engineering (RE), a critical phase in software development, involves gathering and defining software requirements. However, research on the impact of GenAI and LLMs within RE remains limited. This paper examines the adoption of GenAI in RE, with the aim of exploring its practical implications, identifying current research trends, and highlighting areas for future development. To achieve this, a systematic literature review was conducted, addressing three research questions and analyzing 44 studies published over the past decade. The findings reveal that GenAI models, especially LLMs, are extensively employed in a variety of RE tasks, underscoring the versatility and potential of LLMs in enhancing the RE process.
引用
收藏
页码:188 / 194
页数:7
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