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Systematic Literature Review of Prompt Engineering Patterns in Software Engineering

88 Citations2024
Yuya Sasaki, H. Washizaki, Jialong Li
2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC)

A pioneering 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.

Abstract

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.