4 papers
Smaller Models, Unexpected Costs: Trade-offs in LLM Quantization for Automated Program Repair
Fernando Vallecillos-Ruiz, Giordano d'Aloisio, Max Hort +3
Large Language Models (LLMs) are powerful tools and have been increasingly adopted for complex software engineering tasks. As the number of parameters increases, results can often…
A Kernel-Based Approach for Accurate Steady-State Detection in Performance Time Series
Martin Beseda, Vittorio Cortellessa, Daniele Di Pompeo +2
This paper addresses the challenge of accurately detecting the transition from the warmup phase to the steady state in performance metric time series, which is a critical step for…
Investigating Execution-Aware Language Models for Code Optimization
Federico Di Menna, Luca Traini, Gabriele Bavota +1
Code optimization is the process of enhancing code efficiency, while preserving its intended functionality. This process often requires a deep understanding of the code execution b…
On the Compression of Language Models for Code: An Empirical Study on CodeBERT
Giordano d'Aloisio, Luca Traini, Federica Sarro +1
Language models have proven successful across a wide range of software engineering tasks, but their significant computational costs often hinder their practical adoption. To addres…