Automated Assessment of Quality of Jupyter Notebooks Using Artificial Intelligence and Big Code

We present in this paper an automated method to assess the quality of Jupyter notebooks. The quality of notebooks is assessed in terms of reproducibility and executability. Specifically, we automatically extract a number of expert-defined features for each notebook, perform a feature selection step,...

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Bibliografske podrobnosti

Principais autores:	Priti Oli, Rabin Banjade, Lasang Jimba Tamang, Vasile Rus
Format:	Artigo
Jezik:	Inglês
Izdano:	LibraryPress@UF 2021-04-01
Serija:	Proceedings of the International Florida Artificial Intelligence Research Society Conference
Teme:	jupyter notebooks quality assessment big code reproducibility executability machine learning deep learning
Online dostop:	https://journals.flvc.org/FLAIRS/article/view/128560
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