Characterising Bugs in Jupyter Platform

TL;DR

This study analyzes 387 bugs in the Jupyter platform, classifying them into root causes and symptoms, providing insights for developers to improve its correctness, security, and robustness.

Contribution

It is the first comprehensive investigation of bugs in the Jupyter hosting platform, offering a detailed classification and new directions for bug detection and fixing tools.

Findings

Bugs are classified into 11 root causes and 11 symptoms.

Identified 14 major findings to assist developers.

Provides new directions for bug detection and repair tools.

Abstract

As a representative literate programming platform, Jupyter is widely adopted by developers, data analysts, and researchers for replication, data sharing, documentation, interactive data visualization, and more. Understanding the bugs in the Jupyter platform is essential for ensuring its correctness, security, and robustness. Previous studies focused on code reuse, restoration, and repair execution environment for Jupyter notebooks. However, the bugs in Jupyter notebooks' hosting platform Jupyter are not investigated. In this paper, we investigate 387 bugs in the Jupyter platform. These Jupyter bugs are classified into 11 root causes and 11 bug symptoms. We identify 14 major findings for developers. More importantly, our study opens new directions in building tools for detecting and fixing bugs in the Jupyter platform.