3 citations · 4 across the 6 of their papers we have counts for
4 papers · 1 filter
From Code Smells to Best Practices: Tackling Resource Leaks in PyTorch, TensorFlow, and Keras
Bashar Abdallah, Martyna E. Wojciechowska, Gustavo Santos +4
Much of the existing ML research focuses on model performance metrics, leaving limited attention to the long-term sustainability and resource efficiency of ML applications. While h…
RefAgent: A Multi-agent LLM-based Framework for Automatic Software Refactoring
Khouloud Oueslati, Maxime Lamothe, Foutse Khomh
Large Language Models (LLMs) have substantially influenced various software engineering tasks. Indeed, in the case of software refactoring, traditional LLMs have shown the ability…
An Empirical Study on Method-Level Performance Evolution in Open-Source Java Projects
Kaveh Shahedi, Nana Gyambrah, Heng Li +2
Performance is a critical quality attribute in software development, yet the impact of method-level code changes on performance evolution remains poorly understood. While developer…
From Technical Excellence to Practical Adoption: Lessons Learned Building an ML-Enhanced Trace Analysis Tool
Kaveh Shahedi, Matthew Khouzam, Heng Li +2
System tracing has become essential for understanding complex software behavior in modern systems, yet sophisticated trace analysis tools face significant adoption gaps in industri…