FUSION
FUnctionality Sharing In Open eNvironments
Heinz Nixdorf Chair for Distributed Information Systems
 

ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks

Title: ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks
Authors: Sheeba Samuel and Birgitta König-Ries
Source: Provenance Week 2020
Place: Charlotte, North Carolina, USA
Date: 2020-06-22
Type: Publication
Abstract:

Computational notebooks have gained widespread adoption
among researchers from academia and industry as they support reproducible science. These notebooks allow users to combine code, text, and visualizations for easy sharing of experiments and results. They are widely shared in GitHub, which currently has more than 100 million repositories making it the largest host of source code in the world. Recent reproducibility studies have indicated that there exist good and bad practices in writing these notebooks which can affect
their overall reproducibility. We present ReproduceMeGit, a
visualization tool for analyzing the reproducibility of Jupyter
Notebooks. This will help repository users and owners to reproduce and directly analyze and assess the reproducibility of any GitHub repository containing Jupyter Notebooks. The tool provides information on the number of notebooks that were successfully reproducible, those that resulted in exceptions, those with different results from the original notebooks, etc. Each notebook in the repository along with the provenance information of its execution can also be exported in RDF with the integration of the ProvBook tool.

Slides: ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks
URL: http://arxiv.org/abs/2006.12110
BibTex:
@article{DBLP:journals/corr/abs-2006-12110,
  author    = {Sheeba Samuel and
               Birgitta K{\"{o}}nig{-}Ries},
  title     = {ReproduceMeGit: {A} Visualization Tool for Analyzing Reproducibility
               of Jupyter Notebooks},
  journal   = {CoRR},
  volume    = {abs/2006.12110},
  year      = {2020},
  url       = {https://arxiv.org/abs/2006.12110},
  archivePrefix = {arXiv},
  eprint    = {2006.12110},
  timestamp = {Tue, 23 Jun 2020 17:57:22 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2006-12110.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}