35 citations · 74 across the 10 of their papers we have counts for
11 papers
Evaluating Change Point Detection Methods for Software Performance Regression Analysis
Diego Elias Costa, Michele Tucci, Luca Traini +8
Performance issues in software systems are a critical quality issue that can erode user trust, violate service-level agreements, and ultimately affect business efficiency. Conseque…
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…
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…