@article{siddik_slr_notebook,

title = {A Systematic Literature Review of Software Engineering Research on Jupyter Notebook},

author = {Md Saeed Siddik and Hao Li and Cor-Paul Bezemer},

year  = {2025},

date = {2025-12-27},

urldate = {2025-12-27},

journal = {Journal of Systems and Software},

abstract = {Context: Jupyter Notebook has emerged as a versatile tool that transforms

how researchers, developers, and data scientists conduct and communicate

their work. As the adoption of Jupyter notebooks continues to rise, so does

the interest from the software engineering research community in improving

the software engineering practices for Jupyter notebooks.

Objective: The purpose of this study is to analyze trends, gaps, and

methodologies used in software engineering research on Jupyter notebooks.

Method : We selected 199 relevant publications up to September 2025,

following established systematic literature review guidelines. We explored

publication trends, categorized them based on software engineering topics,

and reported findings based on those topics.

Results: The most popular venues for publishing software engineering

research on Jupyter notebooks are related to human-computer interaction

instead of traditional software engineering venues. Researchers have ad-

dressed a wide range of software engineering topics on notebooks, such as

code reuse, readability, and execution environment. Although reusability is

one of the research topics for Jupyter notebooks, only 82 of the 199 studies

can be reused based on their provided URLs. Additionally, most replication

packages are not hosted on permanent repositories for long-term availability

and adherence to open science principles.

Conclusion: Solutions specific to notebooks for software engineering is-

sues, including testing, refactoring, and documentation, are underexplored.

Future research opportunities exist in automatic testing frameworks, refac-

toring clones between notebooks, and generating group documentation for

coherent code cells.},

keywords = {Jupyter Notebook, SLR},

pubstate = {published},

tppubtype = {article}

}