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arXiv · 2606.23877

JupOtter: Cell-Level Bug Detection in Jupyter Notebooks

Lukas Ottenhof·Thibaud Lutellier
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Abstract

Jupyter Notebooks are an increasingly popular coding environment used across many domains, especially in Python-based data science and scientific computing. Originally used for prototyping and interactive exploration, notebooks are increasingly used to develop more complex programs, leading to a rapid rise in buggy notebooks on platforms like GitHub. To address this trend, we present JupOtter, a bug detection system designed specifically for Jupyter Notebooks. JupOtter features three novel contributions: (1) a notebook-specific tokenization strategy that preserves cell structure, (2) a cell-level bug prediction technique, and (3) a new labeled dataset, OtterDataset, containing over 21,000 notebooks annotated for fine-grained cell-level bug detection. JupOtter achieves cell-level bug detection F1 scores that surpass static analyzers and large language models in two out of three evaluation datasets.

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Lukas Ottenhof, Thibaud Lutellier. 2026-06-22. JupOtter: Cell-Level Bug Detection in Jupyter Notebooks. https://arxiv.org/abs/2606.23877

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