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, creating 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.

中文翻译：

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恢复Jupyter Notebook的执行环境

超过90％的已发布Jupyter笔记本没有声明对外部软件包的依赖性。这使它们不可执行，从而阻碍了科学结果的可重复性。我们介绍SnifferDog，一种方法：1）收集Python软件包和版本的API，创建API数据库；2）分析笔记本以确定所需软件包和版本的候选者；3）检查使笔记本计算机可执行所需的软件包（理想情况下，重现其存储的结果）。在评估中，我们表明SnifferDog可以为大多数笔记本精确还原执行环境，从而使它们可以立即供最终用户执行。