Background Jupyter notebooks facilitate the bundling of executable code with its
documentation and output in one interactive environment, and they represent a popular …

Jupyter notebooks have become indispensable tools for data analysis and processing in
various domains. However, despite their widespread use, there is a notable research gap in …

Jupyter notebooks have emerged as the predominant tool for data scientists to develop and
share machine learning solutions, primarily using Python as the programming language …

In light of the growing interest in type inference research for Python, both researchers and
practitioners require a standardized process to assess the performance of various type …

The application of Large Language Models (LLMs) in software engineering, particularly in
static analysis tasks, represents a paradigm shift in the field. In this paper, we investigate the …

Computational notebooks have become the primary coding environment for data scientists.
However, research on their code quality is still emerging, and the code shared is often of …

Modern programming languages promote software reuse via package managers that
facilitate the integration of inter-dependent software libraries. Software reuse comes with the …

Jupyter Notebook is an interactive development environment commonly used for rapid
experimentation of machine learning (ML) solutions. Describing the ML activities performed …

Recent advancements in AI and data science have led to the increased use of Jupyter
notebooks. As such, various AI-Based automated tools have been also developed to …

In this paper, we outline potential ways for the further development of computational
notebooks in Integrated Development Environments (IDEs). We discuss notebooks …