Prompt engineering applied to code generation: a preliminary systematic review

Abstract

This Systematic Literature Review examines prompt engineering in automatic code generation using large language models (LLMs). A methodological protocol identified 26 relevant primary studies to characterize the status, trends, challenges, and opportunities of prompt engineering in software development. The results show that prompt engineering has been established as a key discipline for optimizing interaction with LLMs and improve the accuracy, robustness, and applicability of the generated code. The findings were grouped into six recurring thematic categories: structured methodologies, pedagogical strategies, accuracy and robustness, code improvement techniques, security through prompts, and the relevance of prompt engineering in the interaction with LLMs. It also highlights that the accelerated growth of publications between 2021 and 2025, as well as the sustained academic interest, reflect the strategic value of prompt engineering in the software lifecycle. This review provides a critical knowledge base for researchers and developers seeking to integrate prompt engineering into their processes and practices effectively.