标题： 观察开发过程中Jupyter笔记本中的细粒度变化 显示英文标题

标题： Observing Fine-Grained Changes in Jupyter Notebooks During Development Time

摘要： 在软件工程中，许多研究集中在细粒度日志的分析上，这在重构、安全性和代码补全等领域带来了重要的创新。 然而，在数据科学背景下，针对计算笔记本的类似研究尚未开展。 为了弥补这一研究空白，我们做出了三项科学贡献：我们 (1) 引入了一个工具集，用于在开发过程中收集Jupyter笔记本中的代码更改；(2) 使用它收集了与数据分析任务和机器学习任务相关的超过100小时的工作（由20名不同专业水平的开发人员完成）， resulting in a dataset containing 2,655 cells and 9,207 cell executions; 并且 (3) 使用此数据集来研究笔记本开发过程的动态性质以及笔记本中发生的变化。 在对收集到的数据进行分析时，我们将执行之间的单元格更改进行了分类，并发现其中相当一部分更改是相对较小的修复和代码迭代修改。 这表明笔记本不仅用作开发和探索工具，还用作调试工具。 我们报告了一些其他见解，并提出了关于新数据的潜在未来研究方向。 显示英文摘要

摘要： In software engineering, numerous studies have focused on the analysis of fine-grained logs, leading to significant innovations in areas such as refactoring, security, and code completion. However, no similar studies have been conducted for computational notebooks in the context of data science. To help bridge this research gap, we make three scientific contributions: we (1) introduce a toolset for collecting code changes in Jupyter notebooks during development time; (2) use it to collect more than 100 hours of work related to a data analysis task and a machine learning task (carried out by 20 developers with different levels of expertise), resulting in a dataset containing 2,655 cells and 9,207 cell executions; and (3) use this dataset to investigate the dynamic nature of the notebook development process and the changes that take place in the notebooks. In our analysis of the collected data, we classified the changes made to the cells between executions and found that a significant number of these changes were relatively small fixes and code iteration modifications. This suggests that notebooks are used not only as a development and exploration tool but also as a debugging tool. We report a number of other insights and propose potential future research directions on the novel data.