发表机构
Inria / Univ. Lille / CNRS, CRIStAL（法国国家信息与自动化研究所/里尔大学/CNRS，CRIStAL）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
Joule-Profiler是一款开源命令行工具，通过Intel RAPL和NVML测量硬件能耗，并基于标准输出归因到用户定义阶段，实现对Maven构建流水线（以Gson为例）的分阶段能耗分析，比较冷热构建差异。
AI 中文摘要
构建流水线是现代软件开发中不可或缺的一部分，然而其能耗足迹对实践者来说在很大程度上仍然不可见。现有的CI能耗工具要么依赖于基于模型的估算（由于云运行器中的硬件访问限制），要么仅报告整个流水线的总能耗，而不将其分解为有意义的阶段。Joule-Profiler是一个开源的Linux命令行工具，通过Intel RAPL（CPU）和NVML（NVIDIA GPU）测量硬件能耗，并通过监控标准输出将其归因于用户定义的程序阶段。在这篇工具论文中，我们以Google Gson作为案例研究，在Maven构建流水线的背景下演示了Joule-Profiler。通过应用令牌模式匹配的Maven插件调用，我们分析了Gson最近5个版本的构建，生成每个阶段的能耗概况，并比较了冷构建（空本地仓库）和热构建（缓存依赖）的情况。
英文摘要
Build pipelines are integral to modern software development, yet their energy footprint remains largely invisible to practitioners. Existing CI energy tools either rely on model-based estimation (due to hardware access restrictions in cloud runners) or report only total pipeline energy without decomposing it into meaningful phases. Joule-Profiler is an open-source command-line tool for Linux that measures hardware energy consumption via Intel RAPL (CPU), NVML (NVIDIA GPU), and attributes it to user-defined program phases by monitoring standard output. In this tool paper, we demonstrate Joule-Profiler in the context of Maven build pipelines using Google Gson as a case study. By applying a token pattern-matching Maven plugin invocations, we analyze builds across the 5 most recent Gson releases into per-phase energy profiles, comparing cold builds (empty local repository) and warm builds (cached dependencies).
Comments4 pages, 2 figures. Submitted to the ICSE 2027 Tool Demonstration and Data Showcase Track
