12 papers · 1 filter
Observing the Conduct of Systematic Reviews with Generative AI Support: An Experience Report from a Graduate Software Engineering Course
Danilo Monteiro Ribeiro, Gilberto Sussumu Hida
Context: Secondary studies are fundamental practices in Evidence- Based Software Engineering, but teaching them requires activities that expose students to authentic methodological…
Understanding LLM Usage Among Early-Career Software Engineers in Practice
Julia Alencar, Ronnie de Souza Santos, Italo Santos +2
Despite the rapid adoption of Large Language Models in professional software engineering, limited research has investigated how early career professionals develop effective AI assi…
Factors Impacting Developer Efficiency: Results from an Adaptive Longitudinal Study
Danilo Ribeiro, Breno Alves, Gabriel Souza +2
Context: Developer efficiency is driven by technical, organizational, and personal factors, yet few longitudinal studies explore how these factors evolve over time. Objective: This…
ADEMM: A Longitudinal Method for Monitoring Developer Efficiency in Industry
Danilo Ribeiro, Breno Alves, Gabriel Souza +2
Context: Developer efficiency is influenced by technical, organizational, cognitive, and communication-related factors. However, most studies rely on one-time assessments or fixed…
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…
Useful Learning Experiences: A Qualitative Study of Corporate Training in Brazilian Software Engineering
Rodrigo Siqueira, Antonio Oliveira, Breno Alves de Andrade +2
Context: Quantitative studies can identify statistical predictors of training quality, but they often fail to capture what professionals themselves consider genuinely useful learni…
The professional's opinion: Suggestions for improving the corporate education training process in Software Engineering
Rodrigo Siqueira, Danilo Monteiro Ribeiro
Technology organizations continuously invest in professional development, but face difficulties in transferring learning to project practice. This exploratory qualitative study inv…