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June 5, 2026Journal of Systems and Software0 citationsOpen Access

Energy-aware decision making in software stack upgrades

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MSMirko StockerMWMichael Wahler

Key Points

  • This research aims to understand how software stack upgrades impact energy consumption, crucial for sustainable practices.
  • Developed a systematic method to measure energy consumption of software stack components.
  • Conducted automated benchmarking with different versions of Spring Boot and JVM on the Spring Petclinic REST application.
  • Evaluated the influence of framework versions, runtime versions, and execution platforms on energy usage.
  • Energy consumption varies significantly across different versions of Spring Boot and JVM.
  • Newer JVM releases and virtual threads offered substantial energy savings without needing application modifications.
  • Identified unexpected regressions in energy usage with some version combinations, highlighting the complexity of upgrades.

Abstract

Software stack upgrades are a routine part of software maintenance and evolution, typically motivated by improved performance, stability, or functionality. Yet their impact on energy consumption —a growing concern for organizations pursuing sustainability—remains poorly understood. This paper presents a systematic method for measuring how different versions of core software stack components, such as Spring Boot and the Java Virtual Machine (JVM), influence the energy consumption of applications. Our approach evaluates combinations of framework versions, runtime versions, and execution platforms through automated benchmarking. Using a case study based on the Spring Petclinic REST application, we show that energy consumption varies substantially across Spring Boot and JVM versions, in some cases producing unexpected regressions. Notably, newer JVM releases and virtual threads (introduced in Java 21 and 23) yielded significant energy savings without requiring application changes. These results demonstrate that software upgrades can meaningfully affect energy usage and that measuring energy consumption provides valuable evidence for decision making in software maintenance and evolution.

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Cite This Study

Stocker et al. (2026) studied this question.

synapsesocial.com/papers/6a22672f763171746d545eachttps://doi.org/10.1016/j.jss.2026.112963
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