Measuring Software Energy Consumption

Group 1: Comparing Energy Consumption of Popular RegEx Engines in Text Editors and IDEs
By Marina Escribano Esteban, Kevin Hoxha, Inaesh Joshi, Todor Mladenović .
This study evaluates the energy efficiency of RegEx engines across JavaScript, Java, .NET, and C++. It analyses their performance at varying complexity levels. Results show that JavaScript consiste…

Group 2: TensorFlow, Torch and JAX energy consumption comparison for convolutional neural networks on MNIST
By Reinier Schep, Maosheng Jiang, Razvan Loghin and Alex Zheng .
TensorFlow, Torch and JAX energy consumption comparison for convolutional neural networks on MNIST dataset.

Group 3: Comparing energy consumption between the Cycles rendering engine in Blender
By Matthijs Vossen, Melle Koper, Scott Jochems, Roan Rosema .
In modern digital content creation pipelines, rendering can be a major bottleneck—not only in terms of time but also energy consumption. As sustainability becomes a priority, understanding the ener…

Group 4: The browser energy efficiency revolution
By Anyan Huang, Yongcheng Huang, Yiming Chen, Philippe Henry, .
This study investigates the energy consumption of two popular web browsers, Google Chrome and Mozilla Firefox, under realistic user scenarios on macOS, Linux and Windows. By modeling activities suc…

Group 5: Investigating how using uBlock Origin affects energy consumption
By Jort van Driel, Dorian Erhan, Weicheng Hu, Giannos Rekkas .
This study evaluates the energy consumption of web browsers under different configurations and environments. Specifically, we compare Chrome with two conditions: using no extension and using uBloc…

Group 6: Measuring the Energy Consumption of Large Language Models: A Deep Dive
By Rafał Owczarski,Lászlo Roovers Athanasios Christopoulos, Zain Fazal .
We explore the energy consumption patterns of Large Language Models (LLMs) during inference, focusing on local machine usage rather than cloud environments. We aim to identify dependencies between …

Group 7: Energy Consumption in PDF Readers: A Comparative Analysis
By Ahmed Driouech, Ahmed Ibrahim, Taoufik el Kadi, Moegiez Bhatti .
PDF readers are a widely used software tool, especially for students who spend considerable time reading e-books and study materials. This project explores the energy consumption of different PDF r…

Group 8: Comparing the Energy Consumption of Different Database Management Systems
By Kevin Chen, Tibieru Sabău, Floris van Veen, Kah Ming Wong .
This blog aims to compare the energy output between two different database management systems: MySQL and PostgreSQL to find which of the two is more energy efficient, and if this still holds when t…

Group 9: Energy Efficiency of Search Engines
By Ilma Jaganjac, Angelos-Ermis Mangos, Marvin Blommestijn, Pravesha Ramsundersingh .
This study examines the energy consumption of various search engines from a user’s perspective, focusing on power usage, response time, and efficiency. By measuring energy consumption during search…

Group 10: Minecraft Energy Consumption Comparison with and without Shaders
By Andrea Onofrei, Ayush Kuruvilla, Sahar Marossi, Yulin Chen .
This article presents a roadmap on how to properly set up a scientific methodology to measure energy consumption in Minecraft with and without shaders. We outline unbiased energy measurement strat…

Group 11: Comparing Energy Consumption of Spring Boot and Dropwizard
By Ana Țerna, Andrei-Iulian Vișoiu, Lucian Toșa, Monica Păun .
An analysis of two popular Java-based frameworks, Spring Boot and Dropwizard, was conducted along the lines of the report. The comparison was outlined by starting up an application that handles GE…

Group 12: Measuring energy consumption of SQL databases
By Simon Biennier, Jasper Heijne, Paul Lindhorst, Huib Sprangers .
In this paper we analyse the difference in energy consumption between usage of MySQL and SQLite to give insights for developers in the development phase of the database. After running our experimen…

Group 13: Sustainable Servers: Benchmarking energy consumption of various backend frameworks
By Sofia Konovalova (6174019), Kaijen Lee (5100887), Violeta Macsim (5498031) .
In the emerging digital age, servers consume more energy to provide data to people. While physical components consume the majority of energy, is there anything you can do as a developer to cut back…

Group 14: Jellyfin: Web Browser vs. Native App Energy Consumption Comparison
By Joaquín Cava, Elena Ibañez, Roelof van der Geest, Jeroen Janssen .
Jellyfin is a free open-source media system designed to watch your own videos from anywhere. We compare the energy usage of the web interface vs. the native app on various codecs.

Group 15: Energy Efficiency in Text Editors: A Comparative Analysis
By Raghav Talwar, Peiyan Liu, Shalakha Rudrapatna Suresh, Konrad Barbers .
Developers use text editors for a lot of everyday tasks. Even though these tasks are usually quick and easy, all the time spent using the editor can really add up in terms of energy use. The report…

Group 16: Comparing Energy Consumption of Note-Taking Applications
By Mirko Boon, Reeve Lorena, Gopal-Raj Panchu, Sotiris Vacanas .
In this experiment we compared the energy efficiency of different text-editing applications to evaluate which common text-editor is most efficient. We have found that notepad++ is significantly mor…

Group 18: Comparing the Energy Consumption of Different Machine Learning Libraries
By Gyum Cho, Denis Krylov, Ciprian Bîcă, Matteo Fregonara .
We investigate the energy consumption differences between three popular Python machine learning libraries (PyTorch, TensorFlow, and JAX) when implementing identical neural network architectures. JA…

Group 19: Investigating the impact of extensions on power usage of VS Code
By Aline Mol, Duyemo Anceaux, Kris van Melis, Max de Groot .
This study investigates the impact of running Visual Studio Code (VSCode) extensions on power usage during startup. Through controlled experiments measuring energy consumption across different exte…

Group 20: Energy consumption comparison between different graphics settings in GTA V
By Seyidali Bulut, Johan van den Berg, Michal Kuchar, Artin Sanaye .
This experiment analyses the energy consumption of GTA V under different graphics settings to determine the increase in energy usage from low to high settings. To ensure our results are not depende…

Group 21: Monitoring energy consumption for sorting algorithms in Java, C++ and Python
By Wout Burgers, Martijn Frericks, David van der Maas, Thomas Rooskens .
This study compares the energy consumption, power usage, and execution times of four sorting algorithms—Bubble Sort, Counting Sort, Merge Sort, and Radix Sort—implemented in Python, Java, and C++. …

Group 22: Comparing H.264 and H.265 video decoding energy consumption
By Michael Chan, Roberto Negro, Jamila Seyidova, Gijs Margadant .
This study explores the energy consumption of video decoding for H.264 and H.265 across different resolutions. The findings provide insights into the impact of video codecs on device efficiency and…

Group 23: Comparing the energy efficiency of different LLM inference runtimes
By Victor Hornet, Elena Mihalache, Andreea Mocanu, Alexandru Postu, Kian Sie .
As the adoption of Large Language Models (LLMs) continues to grow across various applications, selecting the most energy-efficient models is crucial for minimizing energy consumption. This article …

Group 24: Energy Consumption Comparison: Python 3.14 vs Python 3.11
By Luc Dop, Sabina Grădinariu, Nawmi Nujhat, Vincent van Vliet .
This study explores the energy consumption differences between Python 3.14 and Python 3.11, testing the claim that Python 3.14 has a 30% speed improvement over previous versions. We run the same co…

Group 25: Native vs. Web: Analysing the Energy Consumption of Spotify Apps
By Julian Hirschler, Patrick Krumpl, Shantanu Jare, Sven Butzelaar, Thomas Verwaal .
In this project we compare the spotify native and web app by looking at the energy consumption when playing songs. Spotify has 675 million monthly active users and thus has a significant environmen…

Group 9000: Title of the template blog
By Student1 first and last name, Student2, Student3 .
abstract Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco labo…

How to contribute

To add a new article, follow the instructions below:

Fork the repo of the website on Github: https://github.com/luiscruz/course_sustainableSE/
Create a new markdown file inside the directory 2025/p1_measuring_software
- Use the following filename format: g<group_number>_<1/2meaningful_keywords>.md
- Use the file gX_template.md as a template
- If you want to add images, add it to 2025/img/p1_measuring_software/g<group_number>_<1/2meaningful_keywords>/
Commit, Push.
Submit a pull request.

Before submitting the pull request, you should test whether your file is rendering properly in the website. The easiest way to check it is by running the docker container, as instructed in the Github Readme.

Your page should be listed here: http://localhost:4000/course_sustainableSE/2025/p1_measuring_software

If you don’t want to deal with jekyll, you can do it the slow and expensive way: 1) enable github pages in your fork repo 2) check your the deployed page. (I don’t recommend it, though)

Note: let me know if you run into any issue or if there’s any step you think should be explained here.