开发者针对软件能耗优化的态度与实践
Developer Attitudes and Practices Towards Optimizing Software Energy Consumption
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中文总结 AI 辅助
该研究通过对134名开发者的调查，揭示了软件能耗在开发中未受足够重视的现状、存在的盲区及阻碍，提出了制度化方法、扩展相关研究教育、开发实用工具等建议。
中文摘要 AI 辅助
背景：软件对硬件资源利用效率有显著影响，但在日常开发实践中，软件能耗很少被视为一级关注点。目的：本研究调查专业开发者与软件能耗相关的态度、决策及开发实践，重点关注软件开发过程中如何识别、评估和处理能耗问题。方法：为此，我们开展了一项包含134名软件开发者的在线调查，结合定量分析与自由文本回复的定性开放卡片分类，以刻画围绕能耗的认知、实践及推理模式。发现：仅少数项目明确考虑能耗，开发者更常通过优化执行时间、CPU利用率等代理属性间接影响能耗；对情景类问题的回复显示该思维模式存在系统性盲区，包括性能提升反而增加能耗或无相关性的情况；还识别出组织层面的阻碍、工具有限、教育缺口是采用的主要障碍。启示：（1）通过展示价值的标志性部署将能耗感知方法制度化；（2）扩展能耗-性能权衡的研究与教育；（3）开发面向开发者的实用测量与反馈工具，降低采用门槛。
英文摘要
Context: Software significantly influences the efficiency with which hardware resources are utilized, yet software energy consumption is seldom treated as a first-class concern in day-to-day development practice. Objective: This study investigates professional developers' attitudes, decision-making, and development practices related to software energy consumption, with particular emphasis on how energy considerations are recognized, assessed, and acted upon during software development. Method: To this end, we conduct an online survey with 134 software developers. Our study combines quantitative analyses with a qualitative open-card sorting of free-text responses to characterize perceptions, practices, and reasoning patterns around energy consumption. Findings: Energy consumption is explicitly considered in only a minority of projects. More commonly, developers influence energy use indirectly by optimizing proxy properties such as execution time and CPU utilization. Responses to scenario-based questions reveal systematic blind spots in this mental model, including cases in which performance improvements increase energy consumption or exhibit no correlation. We also identify organizational disincentives, limited tooling, and educational gaps as major barriers to adoption. Implications: (1) Institutionalize energy-aware approaches through visible flagship deployments that demonstrate value, (2) expand research and education on energy-performance trade-offs, and (3) develop practical, developer-oriented measurement and feedback tools that lower adoption barriers.
发表机构
- Leipzig University（莱比锡大学）
- ScaDS.AI Dresden/Leipzig, Leipzig University（德累斯顿/莱比锡 ScaDS.AI，莱比锡大学）
- Saarland Informatics Campus, Saarland University（萨尔兰信息学校园，萨尔兰大学）
机构由 AI 辅助整理，请以论文原文为准。
