From Specifications to Prompts: On the Future of Generative Large Language Models in Requirements Engineering

被引：3

作者：

Vogelsang, Andreas ^{[1
]}

机构：

[1] Univ Cologne, Software Engn, D-50923 Cologne, Germany

来源：

IEEE SOFTWARE | 2024年 / 41卷 / 05期

关键词：

Large language models; Requirements engineering; Prompt engineering; Task analysis;

D O I：

10.1109/MS.2024.3410712

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Generative LLMs, such as GPT, have the potential to revolutionize Requirements Engineering (RE) by automating tasks in new ways. This column explores the novelties and introduces the importance of precise prompts for effective interactions. Human evaluation and prompt engineering are essential in leveraging LLM capabilities.

引用

页码：9 / 13

页数：5

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