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cs.SE2026

Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code Review

Zhenhan Gao, Marvin Muñoz Barón, Umm-e Habiba +2

Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to understand. Developers struggle to…

cs.SE2025

ReqBrain: Task-Specific Instruction Tuning of LLMs for AI-Assisted Requirements Generation

Mohammad Kasra Habib, Daniel Graziotin, Stefan Wagner

Requirements elicitation and specification remains a labor-intensive, manual process prone to inconsistencies and gaps, presenting a significant challenge in modern software engine…

cs.SE2025

Towards Emotionally Intelligent Software Engineers: Understanding Students' Self-Perceptions After a Cooperative Learning Experience

Allysson Allex Araújo, Marcos Kalinowski, Matheus Paixao +1

[Background] Emotional Intelligence (EI) can impact Software Engineering (SE) outcomes through improved team communication, conflict resolution, and stress management. SE workers f…

cs.SE2024

Overwhelmed Software Developers

Lisa-Marie Michels, Aleksandra Petkova, Marcel Richter +3

We have conducted a qualitative psychology study to explore the experience of feeling overwhelmed in the realm of software development. Through the candid confessions of two partic…

cs.SE2024

Understanding and measuring software engineer behavior: What can we learn from the behavioral sciences?

Allysson Allex Araújo, Marcos Kalinowski, Daniel Graziotin

This paper explores the intricate challenge of understanding and measuring software engineer behavior. More specifically, we revolve around a central question: How can we enhance o…