CISPA
Browse
cispa_all_3827.pdf (3.81 MB)

Restoring reproducibility of Jupyter notebooks

Download (3.81 MB)
conference contribution
posted on 2023-11-29, 18:23 authored by Jianqiang WangJianqiang Wang, Tzu-yang Kuo, Li Li, Andreas ZellerAndreas Zeller
More than ninety percent of published Jupyter notebooks do not state dependencies on external packages. This makes them non-executable and thus hinders reproducibility of scientific results. We present SnifferDog, an approach that 1) collects the APIs of Python packages and versions, creat- ing a database of APIs; 2) analyzes notebooks to determine candidates for required packages and versions; and 3) checks which packages are required to make the notebook executable (and ideally, reproduce its stored results). In its evaluation, we show that SnifferDog precisely restores execution environments for the largest majority of notebooks, making them immediately executable for end users.

History

Preferred Citation

Jiawei Wang, Tzu-yang Kuo, Li Li and Andreas Zeller. Restoring reproducibility of Jupyter notebooks. In: International Conference on Software Engineering (ICSE). 2021.

Primary Research Area

  • Secure Connected and Mobile Systems

Name of Conference

International Conference on Software Engineering (ICSE)

Legacy Posted Date

2022-10-13

Open Access Type

  • Green

Presentation Type

  • Presentation (no conference)

BibTeX

@inproceedings{cispa_all_3827, title = "Restoring reproducibility of Jupyter notebooks", author = "Wang, Jiawei and Kuo, Tzu-yang and Li, Li and Zeller, Andreas", booktitle="{International Conference on Software Engineering (ICSE)}", year="2021", }

Usage metrics

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC