3 papers
cs.SE2026
When Who You Are Can Change the Code You Get: A Study of Persona-Induced Bias in LLM Code Generation
Anubhav Gupta, Mayara Costa Figueiredo, Leticia Santos Machado +4
Large Language Models (LLMs) are widely used as programming assistants, yet it remains unclear whether and how user's demographic information impacts the technical quality of gener…
cs.SE2025
Cracking CodeWhisperer: Analyzing Developers' Interactions and Patterns During Programming Tasks
Jeena Javahar, Tanya Budhrani, Manaal Basha +3
The use of AI code-generation tools is becoming increasingly common, making it important to understand how software developers are adopting these tools. In this study, we investiga…
cs.SE2025
Toward Inclusive AI-Driven Development: Exploring Gender Differences in Code Generation Tool Interactions
Manaal Basha, Ivan Beschastnikh, Gema Rodriguez-Perez +1
The increasing reliance on Code Generation Tools (CGTs), such as Claude Code and GitHub Copilot, is revamping programming workflows and raising critical questions about fairness an…