Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
ChatGPT for Tailoring Software Documentation for Managers and Developers
1
Zitationen
4
Autoren
2025
Jahr
Abstract
Abstract In many agile software development projects, documentation is often missing, outdated, or written with only a technical perspective. Existing literature recognizes the importance of documentation quality, especially when it comes to its readability for diverse audiences. While recent advances in Large Language Models (LLMs) offer the potential to tackle these issues, the use of LLMs for software documentation remains unexplored. This paper investigates the use of ChatGPT to improve and adapt documentation to specific audiences. We apply ChatGPT-4 for alternative documentation production and measure the resulting text characteristics and readability. Twenty-five experts from management and development rate these different versions. Results show the suitability of ChatGPT for generating high-quality text for both audiences, with managers benefiting more from an adapted version.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.393 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.259 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.688 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.502 Zit.