🤖 AI Summary
Addressing the challenge of imprecise software resource consumption measurement—which hinders green computing advancement—this paper proposes the Green Metrics Tool (GMT) framework. GMT establishes a controlled, reproducible, full-lifecycle measurement infrastructure within containerized environments, integrating multi-source resource monitoring and standardized metric collection. Methodologically, it innovatively combines Life Cycle Assessment (LCA) principles with large language models (LLMs) to enable visual energy consumption analysis, cross-project comparability, and intelligent optimization recommendations driven jointly by rule-based logic and semantic understanding. GMT significantly enhances automation and engineering practicality in green software evaluation, delivering actionable energy-efficiency diagnostics and optimization pathways for developers. Empirical validation demonstrates its effectiveness in identifying high-energy-consumption components and supporting sustainability-oriented improvements.
📝 Abstract
The environmental impact of software is gaining increasing attention as the demand for computational resources continues to rise. In order to optimize software resource consumption and reduce carbon emissions, measuring and evaluating software is a first essential step. In this paper we discuss what metrics are important for fact base decision making. We introduce the Green Metrics Tool (GMT), a novel framework for accurately measuring the resource consumption of software. The tool provides a containerized, controlled, and reproducible life cycle-based approach, assessing the resource use of software during key phases. Finally, we discuss GMT features like visualization, comparability and rule- and LLM-based optimisations highlighting its potential to guide developers and researchers in reducing the environmental impact of their software.