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LLMs and Stack Overflow Discussions: Reliability, Impact, and Challenges

Leuson Mario Pedro Da Silva, Jordan S. AMHI et Foutse Khomh

Ensemble de données (2025)

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Abstract

Since the release of ChatGPT in November 2022, the landscape of developer Q&A platforms, particularly Stack Overflow, has undergone significant changes. The ability of large language models (LLMs) to generate immediate, human-like responses to technical questions has started discussions on their potential to replace traditional Q&A platforms. This dataset was collected as part of an empirical study analyzing Stack Overflow questions and evaluating responses generated by ChatGPT and LLaMA.

The dataset supports research aimed at:

Assessing the reliability of LLM-generated answers and their potential long-term impact on platforms like Stack Overflow.

Tracking the evolution of user engagement with Stack Overflow post-ChatGPT’s release. Comparing the performance of ChatGPT and LLaMA across different topics.

Département: Département de génie informatique et génie logiciel
URL de PolyPublie: https://publications.polymtl.ca/64422/
Source: Zenodo
Maison d'édition: CERN
DOI: 10.5281/zenodo.15086541
Autres DOI associés à ce document: 10.5281/zenodo.15086542
URL officielle: https://doi.org/10.5281/zenodo.15086541
Date du dépôt: 04 avr. 2025 16:54
Dernière modification: 08 avr. 2025 07:33
Citer en APA 7: Da Silva, L. M. P., S. AMHI, J., & Khomh, F. (2025). LLMs and Stack Overflow Discussions: Reliability, Impact, and Challenges [Ensemble de données]. Zenodo. https://doi.org/10.5281/zenodo.15086541

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