Greenvolve at SANER 2026

Software is crucial for sustainability. Inefficient software consumes more computational resources, leading to increased energy usage and carbon emissions. As the digital infrastructure scales globally, optimizing software performance becomes essential not only for cost effectiveness but also for reducing environmental impact, which advocates designing, maintaining, and testing software systems that are energy-efficient, resource-conscious, and environmentally sustainable.

As the software evolves, developers often make numerous modifications to the software to address issues or implement new features. However, modifications may unintentionally degrade overall system performance and energy consumption, leading to performance regression. Furthermore, current testing practices are based on system-level evaluations in controlled environments. However, these approaches often struggle to keep up with rapid development cycles, such as those in DevOps, due to their high demands for resources and time.

Recent advances, such as improved cooling systems and the shift from local computing to large-scale data centers, have contributed to greater energy efficiency in software infrastructure. However, the growing demand for machine learning (ML) and artificial intelligence (AI), together with emerging computing technologies, such as quantum computing (QC), may offset these gains with their significant carbon footprint. Despite these challenges, AI and QC also have significant potential to promote sustainability through applications that optimize resource usage and support environmental monitoring.

Therefore, we propose the Greenvolve workshop with the following goals:

Discussing Opportunities for Green Software Engineering. Investigate how sustainability can be a part of software design, architecture, maintenance, and evolution, with a focus on energy efficiency and resource awareness.
Addressing Practical and Technical Challenges. Discuss how to integrate sustainability metrics into existing development and DevOps workflows, especially in fast-paced environments and modern architectures.
Fostering Collaboration. Encourage dialogue and cooperation among researchers and practitioners in the fields of software engineering, AI, quantum computing, and sustainability to share insights, tools, and best practices.
Shaping the Future of Green Software Evolution. Identify open research questions, emerging trends, and future directions in green software, including the role of AI and quantum technologies in reducing the environmental impact of digital infrastructure.

The proposed topics include, but are not limited to:

Accepted papers

Paolo Ferragina and Francesco Tosoni
“The Energy–Throughput Trade-off in Lossless-Compressed Source Code Storage”
Elena Ballesteros-Morallón, Félix García, María Gutiérrez, Mª Ángeles Moraga and Coral Calero
“GREENN: Granular evaluation of Energy Efficiency in Neural Networks”
Carlos Pulido Hernández, María de Los Ángeles Moraga de la Rubia and Félix Óscar García Rubio
“Orchestrating AI-Driven Code Refactoring Based on Energy Measurements in CI Pipelines”
Robert Arntzenius, Xutong Liu and Andy Zaidman
“On The Energy Consumption of Continuous Integration in Open-Source Java Projects”
Maja Hanne Kirkeby and Timmie Lagermann
“Power Assumptions Matter: Revisiting Laptop Energy Models for Sustainability Reporting”
Anas Shatnawi, Benoit Verhaeghe, Boubou Thiam Niang and Louay Khrouf
“Energy Consumption of Web Frontend Frameworks: An Empirical Comparison of Angular and React”
André Brandão, Diogo Matos, Miguel Guimarães, Simão Cunha and João Saraiva
“The Green Side of the Lua”
Kalle Pronk, Qin Zhao and Siebren Kazemier
“Beyond Model Optimization: Practical Energy-Efficient LLM Inference through Context-Aware Input Reduction”
Alessandro Aneggi, Andrea Janes and Xiaozhou Li
“PPTAMη: Energy Aware CI/CD Pipeline for Container Based Applications”

Program


9:00 - 9:15	Welcome and opening message
9:15 - 10:05	Keynote by Weiyi Shang: “Evaluating the efficiency of LLM-generated code”
10:05 - 10:30	The Green Side of the Lua
10:30 - 11:00	Morning coffee break
11:00 - 11:25	The Energy–Throughput Trade-off in Lossless-Compressed Source Code Storage
11:25 - 11:50	On The Energy Consumption of Continuous Integration in Open-Source Java Projects
11:50 - 12:15	Power Assumptions Matter: Revisiting Laptop Energy Models for Sustainability Reporting
12:15 - 12:30	Energy Consumption of Web Frontend Frameworks: An Empirical Comparison of Angular and React
12:30 - 14:00	Lunch
14:00 - 14:15	PPTAMη: Energy Aware CI/CD Pipeline for Container Based Applications
14:15 - 14:40	GREENN: Granular evaluation of Energy Efficiency in Neural Networks
14:40 - 15:05	Orchestrating AI-Driven Code Refactoring Based on Energy Measurements in CI Pipelines
15:05 - 15:30	Beyond Model Optimization: Practical Energy-Efficient LLM Inference through Context-Aware Input Reduction

Keynote

Title: Evaluating the efficiency of LLM-generated code

Abstract: The integration of Large Language Models (LLMs) into software development holds the promise of transforming code generation processes. While AI driven code generation presents numerous advantages for software development, code generated by large language models may introduce sub-optional efficiency of the generated code. In this talk, I will share our recent study on the efficiency of LLM generated code and associated benchmarks. I will also share our initial try out of optimizing efficiency of LLM-generated code.

Weiyi Shang

Bio: Weiyi Shang is an Associate Professor at the University of Waterloo. His research interests include AIOps, big data software engineering, software log analytics and software performance engineering. He serves as a Steering committee member of the SPEC Research Group. He is ranked top worldwide SE research stars in a recent bibliometrics assessment of software engineering scholars. He is a recipient of various premium awards, including the CSCAN-INFOCAN Outstanding Early Career Computer Science Researcher Prize in 2021, the SIGSOFT Distinguished paper award at ICSE 2013, ICSE 2020 and 2025, best paper award at WCRE 2011 and the Distinguished reviewer award for the Empirical Software Engineering journal. His research has been adopted by industrial collaborators (e.g., BlackBerry and Ericsson) to improve the quality and performance of their software systems that are used by millions of users worldwide. Contact him at wshang (at) uwaterloo.ca; uwaterloo.ca/electrical-computer-engineering/profile/wshang.

Call for papers

Topics include, but are not limited to

Green software design, architecture, maintenance, and evolution
Green performance testing and regression detection
Metrics and modeling for green software
Automation and tooling for green software
Benchmarks for performance and sustainability
Green DevOps practices
Empirical studies, case studies, experience reports, and practices on green software
Green AI and machine learning
Quantum computing and sustainability
Carbon footprint assessment and optimization in software

Submission

The workshop welcomes submission of three types of contributions:

Full papers (maximum 8 pages): papers describing mature research results, industrial case studies, or empirical findings related to workshop topics.
Short papers (maximum 4 pages): papers presenting promising ideas, tool descriptions, or initial results for which a full evaluation is not yet available. These may include early-stage research, novel approaches, or innovative applications in practice.
Position papers (maximum 2 pages) visionary papers offering perspectives on the future of performance engineering in the next 5 to 10 years. These papers may address anticipated challenges or emerging trends or call for specific research directions.

Submitted papers must have been neither previously accepted for publication nor concurrently submitted for review in another journal, book, conference, or workshop.

Submissions will undergo a full double-anonymous review process. To be compliant with the double-anonymous policy, submitted papers must adhere to the same rules as those of the Research track of SANER 2026, which can be found here.

All submissions must come in PDF format and conform, at the time of submission, to the IEEE Conference Proceedings Formatting Guidelines (title in 24pt font and full text in 10pt font, LaTEX users must use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf option. IEEE paper templates can be accessed from their official location.

Submitted papers must comply with the IEEE Policy on Authorship.

All submissions must be in English and must not exceed page limits, which include figures and references.

Contributions need to be submitted in PDF format via EasyChair to SANER 2026.

Organizing Committee

Fernando Castor, University of Twente, The Netherlands
Emanuela Guglielmi, University of Molise, Italy
Luana Martins, University of Salerno, Italy
Michele Tucci, SPENCER Lab, University of L’Aquila, Italy

Program Committee

Shaukat Ali, Simula Research Laboratory, Norway
Vasilios Andrikopoulos, University of Groningen, Netherlands
Martin Beseda, University of L’Aquila, Italy
Coral Calero, University of Castilla-La Mancha, Spain
Jácome Cunha, University of Porto and HASLab/INESC TEC, Portugal
Diego Elias Costa, Concordia University, Canada
Daniele Di Pompeo, University of L’Aquila, Italy
Maja H. Kirkeby, Roskilde University, Denmark
Adel Noureddine, University Paris Nanterre, France
Ana Oprescu, University of Amsterdam, Netherlands
João Saraiva, University of Minho and HASLab/INESC TEC, Portugal
Vincenzo Stoico, Vrije Universiteit Amsterdam, Netherlands

Important dates

(All deadlines are 23:59, Anywhere on Earth)

~~Abstract submission: December 12, 2025~~ Not mandatory
Paper submission: December 18, 2025
Authors notification: January 14, 2026
Camera-ready version: January 20, 2026
Workshop dates: March 17, 2026

Contact

For any questions, please don’t hesitate to contact us at: greenvolve2026@easychair.org