9 papers
Class Imbalance and Batch Effects in LLM-Based Screening for Systematic Reviews
Gilberto Sussumu Hida, Danilo Monteiro Ribeiro, Clayton Suguio Hida
This study analyses LLMs in imbalanced binary classification, using study screening in systematic reviews as the application domain. An experiment was conducted in five reviews, co…
What Does It Take to Research with AI? A Rapid Review of Competencies to Train LLM-Literate Researchers
Danilo Monteiro Ribeiro, Ronnie de Souza Santos, Rodrigo Siqueira +5
The growing adoption of Large Language Models in scientific research has created a need to understand what competencies researchers and graduate students require to use these tools…
One Developer Is All You Need: A Case Study of an AI-Augmented One-Person Squad in a Brownfield Enterprise
Marcelo Vilas Boas, Gustavo Pinto, Edward Roberto Monteiro +2
AI tools are enabling engineers to absorb roles previously distributed across cross-functional squads, yet there is little structured evidence on how to design or evaluate such a o…
Beyond Accuracy: LLM Variability in Evidence Screening for Software Engineering SLRs
Gilberto Sussumu Hida, Danilo Monteiro Ribeiro, Erika Yahata
Context: Study screening in systematic literature reviews is costly, inconsistency-prone, and risk-asymmetric, since false negatives can compromise validity. Despite rapid uptake o…
It's Not About Whom You Train: An Analysis of Corporate Education in Software Engineering
Rodrigo Siqueira, Danilo Monteiro Ribeiro
Context: Corporate education is a strategic investment in the software industry, but little is known about how different professional profiles perceive these initiatives. Objective…
Corporate Training in Brazilian Software Engineering: A Quantitative Study of Professional Perceptions
Rodrigo Siqueira, Antonio Oliveira, Breno Alves Andrade +2
Context: Strategic corporate training is essential for the sustained professional development of software engineers. However, there is a knowledge gap regarding the factors that dr…