Developer Attitudes and Practices Towards Optimizing Software Energy Consumption
2026-08-31 • Software Engineering
Software Engineering
AI summaryⓘ
The authors studied how professional software developers think about and handle energy use in their code. They found that only a few developers directly consider energy consumption, often focusing instead on things like speed or CPU use, which don't always save energy. The study also showed that developers face obstacles, such as lack of tools, education, and organizational support, to making energy-efficient software. The authors suggest better education, useful tools, and clear examples to help developers care more about energy use.
software energy consumptionhardware resourcesdeveloper practicesexecution timeCPU utilizationenergy-performance trade-offssoftware optimizationenergy measurement toolssoftware development barriers
Authors
Max Weber, Alina Mailach, Florian Sattler, Sven Apel, Norbert Siegmund
Abstract
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.