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This program is tentative and subject to change.

Fri 2 May 2025 14:30 - 14:45 at 206 plus 208 - Human and Social 4

As machine learning (ML) and artificial intelligence (AI) technologies become more widespread, concerns about their environmental impact are increasing due to the resource-intensive nature of training and inference processes. Green AI advocates for reducing computational demands while still maintaining accuracy. Although various strategies for creating sustainable ML systems have been identified, their real-world implementation is still underexplored. This paper addresses this gap by studying 168 open-source ML projects on GitHub. It employs a novel large language model (LLM)-based mining mechanism to identify and analyze green strategies. The findings reveal the adoption of established tactics that offer significant environmental benefits. This provides practical insights for developers and paves the way for future automation of sustainable practices in ML systems.

This program is tentative and subject to change.

Fri 2 May

Displayed time zone: Eastern Time (US & Canada) change

14:00 - 15:30
14:00
15m
Talk
Beyond the Comfort Zone: Emerging Solutions to Overcome Challenges in Integrating LLMs into Software Products
SE In Practice (SEIP)
Nadia Nahar Carnegie Mellon University, Christian Kästner Carnegie Mellon University, Jenna L. Butler Microsoft Research, Chris Parnin Microsoft, Thomas Zimmermann University of California, Irvine, Christian Bird Microsoft Research
14:15
15m
Talk
Follow-Up Attention: An Empirical Study of Developer and Neural Model Code Exploration
Journal-first Papers
Matteo Paltenghi University of Stuttgart, Rahul Pandita GitHub, Inc., Austin Henley Carnegie Mellon University, Albert Ziegler XBow
14:30
15m
Talk
Do Developers Adopt Green Architectural Tactics for ML-Enabled Systems? A Mining Software Repository Study
SE in Society (SEIS)
Vincenzo De Martino University of Salerno, Silverio Martínez-Fernández UPC-BarcelonaTech, Fabio Palomba University of Salerno
Pre-print
14:45
15m
Talk
Accessibility Issues in Ad-Driven Web Applications
Research Track
Abdul Haddi Amjad Virginia Tech, Muhammad Danish Virginia Tech, Bless Jah Virginia Tech, Muhammad Ali Gulzar Virginia Tech
15:00
7m
Talk
Toward Effective Secure Code Reviews: An Empirical Study of Security-Related Coding Weaknesses
Journal-first Papers
Wachiraphan (Ping) Charoenwet University of Melbourne, Patanamon Thongtanunam University of Melbourne, Thuan Pham University of Melbourne, Christoph Treude Singapore Management University
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