Systematic Literature Review of Prompt Engineering Patterns in Software Engineering

Advancements in large language models (LLMs) are transforming software engineering through innovative prompt engineering strategies. By analyzing prompt-driven enhancements across key software engineering tasks, we present a sys-tematic literature review and a pioneering taxonomy elucidating the pra...

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Bibliographic Details
Published in2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC) pp. 670 - 675
Main Authors Sasaki, Yuya, Washizaki, Hironori, Li, Jialong, Sander, Dominik, Yoshioka, Nobukazu, Fukazawa, Yoshiaki
Format Conference Proceeding
LanguageEnglish
Published IEEE 02.07.2024
Subjects
large language model
Large language models
LLM application
Prompt engineering
Software
software engineering
Software measurement
sys-tematic literature review
Taxonomy
Technological innovation
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Summary:Advancements in large language models (LLMs) are transforming software engineering through innovative prompt engineering strategies. By analyzing prompt-driven enhancements across key software engineering tasks, we present a sys-tematic literature review and a pioneering taxonomy elucidating the practical applications of prompt engineering in software engineering. Our taxonomy offers a foundational framework that clarifies the roles of prompt engineering and measures its impact, thereby guiding evolving AI -driven software engineering research and practices.
ISSN:2836-3795
DOI:10.1109/COMPSAC61105.2024.00096