Harnessing Hype to Teach Empirical Thinking: An Experience With AI Coding Assistants
Fuente:
arXiv
Saved in:
| Main Authors: | Wyrich, Marvin, Peitek, Norman, Weis, Kallistos, Apel, Sven |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
From Developer Pairs to AI Copilots: A Comparative Study on Knowledge Transfer
by: Welter, Alisa, et al.
Published: (2025)
by: Welter, Alisa, et al.
Published: (2025)
Evidence Tetris in the Pixelated World of Validity Threats
by: Wyrich, Marvin, et al.
Published: (2024)
by: Wyrich, Marvin, et al.
Published: (2024)
From Restructuring to Stabilization: A Large-Scale Experiment on Iterative Code Readability Refactoring with Large Language Models
by: Peitek, Norman, et al.
Published: (2026)
by: Peitek, Norman, et al.
Published: (2026)
Software Engineering Podcasts: An Empirical Study of Their Potential as a Research Resource
by: Wyrich, Marvin, et al.
Published: (2026)
by: Wyrich, Marvin, et al.
Published: (2026)
How do Humans and LLMs Process Confusing Code?
by: Abdelsalam, Youssef, et al.
Published: (2025)
by: Abdelsalam, Youssef, et al.
Published: (2025)
The Silent Scientist: When Software Research Fails to Reach Its Audience
by: Wyrich, Marvin, et al.
Published: (2025)
by: Wyrich, Marvin, et al.
Published: (2025)
What's in a Software Engineering Job Posting?
by: Wyrich, Marvin, et al.
Published: (2025)
by: Wyrich, Marvin, et al.
Published: (2025)
Fixation-related potentials reveal that confusing program code elicits a late frontal positivity
by: Bergum, Annabelle, et al.
Published: (2024)
by: Bergum, Annabelle, et al.
Published: (2024)
Apples, Oranges, and Software Engineering: Study Selection Challenges for Secondary Research on Latent Variables
by: Wyrich, Marvin, et al.
Published: (2024)
by: Wyrich, Marvin, et al.
Published: (2024)
Beyond Self-Promotion: How Software Engineering Research Is Discussed on LinkedIn
by: Wyrich, Marvin, et al.
Published: (2024)
by: Wyrich, Marvin, et al.
Published: (2024)
40 Years of Designing Code Comprehension Experiments: A Systematic Mapping Study
by: Wyrich, Marvin, et al.
Published: (2022)
by: Wyrich, Marvin, et al.
Published: (2022)
Harnessing the Potential of Gen-AI Coding Assistants in Public Sector Software Development
by: Ng, Kevin KB, et al.
Published: (2024)
by: Ng, Kevin KB, et al.
Published: (2024)
Usage, Effects and Requirements for AI Coding Assistants in the Enterprise: An Empirical Study
by: Vukovic, Maja, et al.
Published: (2026)
by: Vukovic, Maja, et al.
Published: (2026)
Generating Java Methods: An Empirical Assessment of Four AI-Based Code Assistants
by: Corso, Vincenzo, et al.
Published: (2024)
by: Corso, Vincenzo, et al.
Published: (2024)
Multi-Location Software Model Completion
by: Welter, Alisa, et al.
Published: (2026)
by: Welter, Alisa, et al.
Published: (2026)
How Are We Doing With Using AI-Based Programming Assistants For Privacy-Related Code Generation? The Developers' Experience
by: Madampe, Kashumi, et al.
Published: (2025)
by: Madampe, Kashumi, et al.
Published: (2025)
Think Like Human Developers: Harnessing Community Knowledge for Structured Code Reasoning
by: Yang, Chengran, et al.
Published: (2025)
by: Yang, Chengran, et al.
Published: (2025)
Constructive Patterns for Human-Centered Tech Hiring
by: Araújo, Allysson Allex, et al.
Published: (2026)
by: Araújo, Allysson Allex, et al.
Published: (2026)
Pragmatic Reasoning improves LLM Code Generation
by: Cao, Zhuchen, et al.
Published: (2025)
by: Cao, Zhuchen, et al.
Published: (2025)
Detecting Performance-Relevant Changes in Configurable Software Systems
by: Böhm, Sebastian, et al.
Published: (2025)
by: Böhm, Sebastian, et al.
Published: (2025)
RubberDuckBench: A Benchmark for AI Coding Assistants
by: Mohammed, Ferida, et al.
Published: (2026)
by: Mohammed, Ferida, et al.
Published: (2026)
Beyond the Commit: Developer Perspectives on Productivity with AI Coding Assistants
by: Chen, Valerie, et al.
Published: (2026)
by: Chen, Valerie, et al.
Published: (2026)
Assessing AI-Based Code Assistants in Method Generation Tasks
by: Corso, Vincenzo, et al.
Published: (2024)
by: Corso, Vincenzo, et al.
Published: (2024)
Examining the Use and Impact of an AI Code Assistant on Developer Productivity and Experience in the Enterprise
by: Weisz, Justin D., et al.
Published: (2024)
by: Weisz, Justin D., et al.
Published: (2024)
The Impact of AI Coding Assistants on Software Engineering: A Longitudinal Study
by: Vella, Annie, et al.
Published: (2026)
by: Vella, Annie, et al.
Published: (2026)
Lessons from Building StackSpot AI: A Contextualized AI Coding Assistant
by: Pinto, Gustavo, et al.
Published: (2023)
by: Pinto, Gustavo, et al.
Published: (2023)
An Empirical Study of Proactive Coding Assistants in Real-World Software Development
by: Li, Lehui, et al.
Published: (2026)
by: Li, Lehui, et al.
Published: (2026)
Inducing Vulnerable Code Generation in LLM Coding Assistants
by: Zeng, Binqi, et al.
Published: (2025)
by: Zeng, Binqi, et al.
Published: (2025)
Automated Prompt Generation for Code Intelligence: An Empirical study and Experience in WeChat
by: Ji, Kexing, et al.
Published: (2025)
by: Ji, Kexing, et al.
Published: (2025)
Hints Help Finding and Fixing Bugs Differently in Python and Text-based Program Representations
by: Rawal, Ruchit, et al.
Published: (2024)
by: Rawal, Ruchit, et al.
Published: (2024)
Automata Learning -- Expect Delays!
by: Dengler, Gabriel, et al.
Published: (2025)
by: Dengler, Gabriel, et al.
Published: (2025)
Collaborator or Assistant? How AI Coding Agents Partition Work Across Pull Request Lifecycles
by: Jo, Young, et al.
Published: (2026)
by: Jo, Young, et al.
Published: (2026)
Does Co-Development with AI Assistants Lead to More Maintainable Code? A Registered Report
by: Borg, Markus, et al.
Published: (2024)
by: Borg, Markus, et al.
Published: (2024)
Spec-Driven Development:From Code to Contract in the Age of AI Coding Assistants
by: Piskala, Deepak Babu
Published: (2026)
by: Piskala, Deepak Babu
Published: (2026)
Generating User Experience Based on Personas with AI Assistants
by: Huang, Yutan
Published: (2024)
by: Huang, Yutan
Published: (2024)
AI builds, We Analyze: An Empirical Study of AI-Generated Build Code Quality
by: Ghammam, Anwar, et al.
Published: (2026)
by: Ghammam, Anwar, et al.
Published: (2026)
How Agentic AI Coding Assistants Become the Attacker's Shell
by: Liu, Yue, et al.
Published: (2026)
by: Liu, Yue, et al.
Published: (2026)
Do AI Coding Agents Log Like Humans? An Empirical Study
by: Ouatiti, Youssef Esseddiq, et al.
Published: (2026)
by: Ouatiti, Youssef Esseddiq, et al.
Published: (2026)
An Empirical Study on the Impact of Gender Diversity on Code Quality in AI Systems
by: Cynthia, Shamse Tasnim, et al.
Published: (2025)
by: Cynthia, Shamse Tasnim, et al.
Published: (2025)
Engineering Pitfalls in AI Coding Tools: An Empirical Study of Bugs in Claude Code, Codex, and Gemini CLI
by: Zhang, Ruixin, et al.
Published: (2026)
by: Zhang, Ruixin, et al.
Published: (2026)
Similar Items
-
From Developer Pairs to AI Copilots: A Comparative Study on Knowledge Transfer
by: Welter, Alisa, et al.
Published: (2025) -
Evidence Tetris in the Pixelated World of Validity Threats
by: Wyrich, Marvin, et al.
Published: (2024) -
From Restructuring to Stabilization: A Large-Scale Experiment on Iterative Code Readability Refactoring with Large Language Models
by: Peitek, Norman, et al.
Published: (2026) -
Software Engineering Podcasts: An Empirical Study of Their Potential as a Research Resource
by: Wyrich, Marvin, et al.
Published: (2026) -
How do Humans and LLMs Process Confusing Code?
by: Abdelsalam, Youssef, et al.
Published: (2025)