Large Language Models (LLMs) have recently shown remarkable capabilities in various software engineering tasks, spurring the rapid development of the Large Language Models for Software Engineering (LLM4SE) area. However, limited attention has been paid to crafting efficient LLM4SE solutions that demand minimal time and memory resources, as well as green LLM4SE solutions that reduce energy consumption and carbon emissions. This 2030 Software Engineering position paper aims to redirect the focus of the research community towards the efficiency and greenness of LLM4SE, while also sharing potential research directions to achieve this goal. It commences with a brief overview of the significance of LLM4SE and highlights the need for efficient and green LLM4SE solutions. Subsequently, the paper presents a vision for a future where efficient and green LLM4SE revolutionizes the software engineering tool landscape, benefiting various stakeholders, including industry, individual practitioners, and society. The paper then delineates a roadmap for future research, outlining specific research paths and potential solutions for the research community to pursue. While not intended to be a definitive guide, the paper aims to inspire further progress, with the ultimate goal of establishing efficient and green LLM4SE as a central element in the future of software engineering.

翻译：大语言模型（LLMs）近期在各类软件工程任务中展现出卓越能力，推动了“软件工程大语言模型”（LLM4SE）领域的快速发展。然而，目前对构建高效（即需极少时间与内存资源）及绿色（即降低能耗与碳排放）的LLM4SE解决方案的关注仍显不足。本2030软件工程立场论文旨在引导研究界聚焦LLM4SE的效率与绿色性，同时分享实现该目标的潜在研究方向。论文首先简要概述LLM4SE的重要性，并强调对高效绿色LLM4SE解决方案的需求。随后，本文描绘了未来高效绿色LLM4SE将彻底变革软件工程工具生态的愿景，惠及工业界、个体从业者及社会等多元利益相关者。进而，论文规划了未来研究路线图，提出具体研究路径与潜在解决方案供研究界探索。虽无意作为权威指南，本文旨在激发进一步突破，最终目标是将高效绿色LLM4SE确立为软件工程未来的核心要素。