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20242026
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cs.SE2026

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…

cs.SE2025

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…

cs.SE2024

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…

cs.SE2024

AI-driven Java Performance Testing: Balancing Result Quality with Testing Time

Luca Traini, Federico Di Menna, Vittorio Cortellessa

Performance testing aims at uncovering efficiency issues of software systems. In order to be both effective and practical, the design of a performance test must achieve a reasonabl…

cs.SE2024

VAMP: Visual Analytics for Microservices Performance

Luca Traini, Jessica Leone, Giovanni Stilo +1

Analysis of microservices' performance is a considerably challenging task due to the multifaceted nature of these systems. Each request to a microservices system might raise severa…