AI 中文总结
本研究通过系统映射分析2010-2024年390篇Green SE文献，发现2023年起该领域关注度因AI相关研究激增，优化与基准测试为主要研究类型，旨在为SE领域提供能源相关方法与实验实践参考。
AI 中文摘要
能源消耗与气候变化已使可持续性成为软件工程（SE）领域的关键议题，推动了绿色软件工程（Green SE）的兴起。过去15年间，SE领域发布了众多面向可持续软件系统的解决方案，为分析该领域的演进提供了丰富资源。为探究这一情况，我们开展了一项针对2010年至2024年间发表的Green SE研究的系统映射研究。我们共收集到390篇文献，按应用领域（如移动、云、AI）和研究类型（如优化研究、基准测试、文献综述）对其进行分类。此外，我们分析了79篇代表性论文的子集，以对能源测量实验中考虑的关键要素（如硬件、测量、稳定性及可复现性）进行分类。研究发现，SE会议刊载了大部分与能源相关的文献；值得注意的是，Green SE研究自2023年起关注度大幅上升，主要由与AI相关的出版物推动；优化与基准测试是最普遍的研究类型。最终，我们旨在为SE领域告知当前应对能源问题的方法，强调关键实验实践，并倡导为实现更可持续的软件工程持续行动。
英文摘要
Energy consumption and climate change have made sustainability critical in Software Engineering (SE), driving the emergence of Green SE. Over the past 15 years, numerous solutions for sustainable software systems have been published by the SE community, offering a rich resource for analyzing the field's evolution. To explore this, we conducted a systematic mapping study of Green SE research published between 2010 and 2024. We collected 390 publications, categorizing them by application domain (e.g., mobile, cloud, AI) and research type (e.g., optimisation study, benchmarking, literature review Additionally, we analyzed a representative subset of 79 papers to classify the key elements-such as hardware, measurement, stability, and replicability-considered during energy measurement experiments. Our findings indicate that SE conferences host the majority of energy-related literature. Notably, Green SE studies surged in popularity starting in 2023, largely driven by AI-related publications. Optimization and benchmarking emerged as the most prevalent research types. Ultimately, we aim to inform the SE community about current approaches to energy concerns, highlight critical experimental practices, and advocate for continued action toward more sustainable software engineering.
Comments29 pages, 6 figures
