74 citations · 245 across the 20 of their papers we have counts for
22 papers
Aggregating empirical evidence from data strategy studies: a case on model quantization
Santiago del Rey, Paulo Sérgio Medeiros dos Santos, Guilherme Horta Travassos +2
Background: As empirical software engineering evolves, more studies adopt data strategiesapproaches that investigate digital artifacts such as models, source code, or system log…
Addressing Quality Challenges in Deep Learning: The Role of MLOps and Domain Knowledge
Santiago del Rey, Adrià Medina, Xavier Franch +1
Deep learning (DL) systems present unique challenges in software engineering, especially concerning quality attributes like correctness and resource efficiency. While DL models exc…
A Framework for Using LLMs for Repository Mining Studies in Empirical Software Engineering
Vincenzo de Martino, Joel Castaño, Fabio Palomba +2
Context: The emergence of Large Language Models (LLMs) has significantly transformed Software Engineering (SE) by providing innovative methods for analyzing software repositories.…
How do Machine Learning Models Change?
Joel Castaño, Rafael Cabañas, Antonio Salmerón +2
The proliferation of Machine Learning (ML) models and their open-source implementations has transformed Artificial Intelligence research and applications. Platforms like Hugging Fa…
Do Developers Adopt Green Architectural Tactics for ML-Enabled Systems? A Mining Software Repository Study
Vincenzo De Martino, Silverio Martínez-Fernández, Fabio Palomba
As machine learning (ML) and artificial intelligence (AI) technologies become more widespread, concerns about their environmental impact are increasing due to the resource-intensiv…
Impact of ML Optimization Tactics on Greener Pre-Trained ML Models
Alexandra González Álvarez, Joel Castaño, Xavier Franch +1
Background: Given the fast-paced nature of today's technology, which has surpassed human performance in tasks like image classification, visual reasoning, and English understanding…
Identifying architectural design decisions for achieving green ML serving
Francisco Durán, Silverio Martínez-Fernández, Matias Martinez +1
The growing use of large machine learning models highlights concerns about their increasing computational demands. While the energy consumption of their training phase has received…
Lessons Learned from Mining the Hugging Face Repository
Joel Castaño, Silverio Martínez-Fernández, Xavier Franch
The rapidly evolving fields of Machine Learning (ML) and Artificial Intelligence have witnessed the emergence of platforms like Hugging Face (HF) as central hubs for model developm…
GAISSALabel: A tool for energy labeling of ML models
Pau Duran, Joel Castaño, Cristina Gómez +1
Background: The increasing environmental impact of Information Technologies, particularly in Machine Learning (ML), highlights the need for sustainable practices in software engine…
Analyzing the Evolution and Maintenance of ML Models on Hugging Face
Joel Castaño, Silverio Martínez-Fernández, Xavier Franch +1
Hugging Face (HF) has established itself as a crucial platform for the development and sharing of machine learning (ML) models. This repository mining study, which delves into more…
Towards green AI-based software systems: an architecture-centric approach (GAISSA)
Silverio Martínez-Fernández, Xavier Franch, Francisco Durán
Nowadays, AI-based systems have achieved outstanding results and have outperformed humans in different domains. However, the processes of training AI models and inferring from them…
Exploring the Carbon Footprint of Hugging Face's ML Models: A Repository Mining Study
Joel Castaño, Silverio Martínez-Fernández, Xavier Franch +1
The rise of machine learning (ML) systems has exacerbated their carbon footprint due to increased capabilities and model sizes. However, there is scarce knowledge on how the carbon…
Teaching MLOps in Higher Education through Project-Based Learning
Filippo Lanubile, Silverio Martínez-Fernández, Luigi Quaranta
Building and maintaining production-grade ML-enabled components is a complex endeavor that goes beyond the current approach of academic education, focused on the optimization of ML…
Energy Consumption of Automated Program Repair
Matias Martinez, Silverio Martínez-Fernández, Xavier Franch
Automated program repair (APR) aims to automatize the process of repairing software bugs in order to reduce the cost of maintaining software programs. Moreover, the success (given…
Guiding the retraining of convolutional neural networks against adversarial inputs
Francisco Durán López, Silverio Martínez-Fernández, Michael Felderer +1
Background: When using deep learning models, there are many possible vulnerabilities and some of the most worrying are the adversarial inputs, which can cause wrong decisions with…
Which Design Decisions in AI-enabled Mobile Applications Contribute to Greener AI?
Roger Creus Castanyer, Silverio Martínez-Fernández, Xavier Franch
Background: The construction, evolution and usage of complex artificial intelligence (AI) models demand expensive computational resources. While currently available high-performanc…
Software Engineering for AI-Based Systems: A Survey
Silverio Martínez-Fernández, Justus Bogner, Xavier Franch +5
AI-based systems are software systems with functionalities enabled by at least one AI component (e.g., for image- and speech-recognition, and autonomous driving). AI-based systems…
Integration of Convolutional Neural Networks in Mobile Applications
Roger Creus Castanyer, Silverio Martínez-Fernández, Xavier Franch
When building Deep Learning (DL) models, data scientists and software engineers manage the trade-off between their accuracy, or any other suitable success criteria, and their compl…
Management of quality requirements in agile and rapid software development: A systematic mapping study
Woubshet Behutiye, Pertti Karhapää, Lidia Lopez +6
Context:Quality requirements (QRs) describe the desired quality of software, and they play an important role in the success of software projects. In agile software development (ASD…
Practical experiences and value of applying software analytics to manage quality
Anna Maria Vollmer, Silverio Martínez-Fernández, Alessandra Bagnato +3
Background: Despite the growth in the use of software analytics platforms in industry, little empirical evidence is available about the challenges that practitioners face and the v…
Towards Automated Data Integration in Software Analytics
Silverio Martínez-Fernández, Petar Jovanovic, Xavier Franch +1
Software organizations want to be able to base their decisions on the latest set of available data and the real-time analytics derived from them. In order to support "real-time ent…
A Quality Model for Actionable Analytics in Rapid Software Development
Silverio Martínez-Fernández, Andreas Jedlitschka, Liliana Guzmán +1
Background: Accessing relevant data on the product, process, and usage perspectives of software as well as integrating and analyzing such data is crucial for getting reliable and t…