Copertina

Investigating and Designing for Trust in AI-powered Code Generation Tools

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Ruotong, Cheng, Ruijia, Ford, Denae, Zimmermann, Thomas
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Human-Computer Interaction Software Engineering
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Evolution of Programmers' Trust in Generative AI Programming Assistants
di: Shah, Anshul, et al.
Pubblicazione: (2025)

From Teacher to Colleague: How Coding Experience Shapes Developer Perceptions of AI Tools
di: Zakharov, Ilya, et al.
Pubblicazione: (2025)

What Needs Attention? Prioritizing Drivers of Developers' Trust and Adoption of Generative AI
di: Choudhuri, Rudrajit, et al.
Pubblicazione: (2025)

Understanding User Mental Models in AI-Driven Code Completion Tools: Insights from an Elicitation Study
di: Desolda, Giuseppe, et al.
Pubblicazione: (2025)

On the Role and Impact of GenAI Tools in Software Engineering Education
di: Qin, Qiaolin, et al.
Pubblicazione: (2025)

Prototyping with Prompts: Emerging Approaches and Challenges in Generative AI Design for Collaborative Software Teams
di: Subramonyam, Hari, et al.
Pubblicazione: (2024)

CodeA11y: Making AI Coding Assistants Useful for Accessible Web Development
di: Mowar, Peya, et al.
Pubblicazione: (2025)

GeoPandas-AI: A Smart Class Bringing LLM as Stateful AI Code Assistant
di: Merten, Gaspard, et al.
Pubblicazione: (2025)

Generating Complex Code Analyzers from Natural Language Questions
di: Nazari, Amirmohammad, et al.
Pubblicazione: (2026)

Bug Detective and Quality Coach: Developers' Mental Models of AI-Assisted IDE Tools
di: Buono, Paolo, et al.
Pubblicazione: (2025)

Will AI also replace inspectors? Investigating the potential of generative AIs in usability inspection
di: Campos, Luis F. G., et al.
Pubblicazione: (2025)

40 Years of Designing Code Comprehension Experiments: A Systematic Mapping Study
di: Wyrich, Marvin, et al.
Pubblicazione: (2022)

Vibe Coding: Toward an AI-Native Paradigm for Semantic and Intent-Driven Programming
di: Bamil, Vinay
Pubblicazione: (2025)

Examining the Use and Impact of an AI Code Assistant on Developer Productivity and Experience in the Enterprise
di: Weisz, Justin D., et al.
Pubblicazione: (2024)

"I Would Have Written My Code Differently'': Beginners Struggle to Understand LLM-Generated Code
di: Zi, Yangtian, et al.
Pubblicazione: (2025)

Exploring the Output of Software Testing Tools through a Visual Comparative Analysis
di: Lit, Brandon, et al.
Pubblicazione: (2026)

Explainability for Embedding AI: Aspirations and Actuality
di: Weber, Thomas
Pubblicazione: (2025)

More Code, Less Reuse: Investigating Code Quality and Reviewer Sentiment towards AI-generated Pull Requests
di: Huang, Haoming, et al.
Pubblicazione: (2026)

Patterns of Developer Adoption of LLM-Generated Code Refactoring Suggestions
di: Schön, David, et al.
Pubblicazione: (2026)

SPROUT: an Interactive Authoring Tool for Generating Programming Tutorials with the Visualization of Large Language Models
di: Liu, Yihan, et al.
Pubblicazione: (2023)

GazeCopilot: Evaluating Novel Gaze-Informed Prompting for AI-Supported Code Comprehension and Readability
di: Elfares, Yasmine, et al.
Pubblicazione: (2025)

Unlocking Adaptive User Experience with Generative AI
di: Huang, Yutan, et al.
Pubblicazione: (2024)

What If We Work Together? Fostering Reflections on Designer Inclusion in Open Source Software Through Speculative Design
di: Nezhad, Rozhan Hozhabri, et al.
Pubblicazione: (2026)

MLLM-Based UI2Code Automation Guided by UI Layout Information
di: Wu, Fan, et al.
Pubblicazione: (2025)

Generating User Experience Based on Personas with AI Assistants
di: Huang, Yutan
Pubblicazione: (2024)

Perceived Usability of Collaborative Modeling Tools
di: Ren, Ranci, et al.
Pubblicazione: (2024)

Time Warp: The Gap Between Developers' Ideal vs Actual Workweeks in an AI-Driven Era
di: Kumar, Sukrit, et al.
Pubblicazione: (2025)

Envisioning the Next-Generation AI Coding Assistants: Insights & Proposals
di: Nghiem, Khanh, et al.
Pubblicazione: (2024)

Who is to Blame: A Comprehensive Review of Challenges and Opportunities in Designer-Developer Collaboration
di: Zhang, Shutong, et al.
Pubblicazione: (2025)

Teaching Agile Requirements Engineering: A Stakeholder Simulation with Generative AI
di: Schön, Eva-Maria, et al.
Pubblicazione: (2026)

On AI-Inspired UI-Design
di: Wei, Jialiang, et al.
Pubblicazione: (2024)

A Study on Developer Behaviors for Validating and Repairing LLM-Generated Code Using Eye Tracking and IDE Actions
di: Tang, Ningzhi, et al.
Pubblicazione: (2024)

Towards Decoding Developer Cognition in the Age of AI Assistants
di: Haque, Ebtesam Al, et al.
Pubblicazione: (2025)

How Far Are We? The Triumphs and Trials of Generative AI in Learning Software Engineering
di: Choudhuri, Rudrajit, et al.
Pubblicazione: (2023)

Investigating VR Accessibility Reviews for Users with Disabilities: A Qualitative Analysis
di: Wang, Yi, et al.
Pubblicazione: (2025)

Trust Calibration in IDEs: Paving the Way for Widespread Adoption of AI Refactoring
di: Borg, Markus
Pubblicazione: (2024)

"Ohhh, He's the Boss!": Unpacking Power Dynamics Among Developers, Designers, and End-Users in FLOSS Usability
di: Hellman, Jazlyn, et al.
Pubblicazione: (2025)

Gendered Prompting and LLM Code Review: How Gender Cues in the Prompt Shape Code Quality and Evaluation
di: Janzen, Lynn, et al.
Pubblicazione: (2026)

The Evolution of Information Seeking in Software Development: Understanding the Role and Impact of AI Assistants
di: Haque, Ebtesam Al, et al.
Pubblicazione: (2024)

What Makes a Fairness Tool Project Sustainable in Open Source?
di: Mim, Sadia Afrin, et al.
Pubblicazione: (2025)