A Qualitative Study of Cleaning in Jupyter Notebooks

kaestner@cs.cmu.edu (H. Dong)
Mon, 18 Oct 2021 08:37:56 GMT

Helen Dong. A Qualitative Study of Cleaning in Jupyter Notebooks. In Proceedings of the European Software Engineering Conference and ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE-SRC), pages 1663--1665, New York, NY: ACM Press, 2021. ESEC/FSE Student Research Competition.

Data scientists commonly use computational notebooks because they provide a good environment for testing multiple models. However, once the scientist completes the code and finds the ideal model, the data scientist will have to dedicate time to clean up the code in order for others to understand it. In this paper, we perform a qualitative study on how scientists clean their code in hopes of being able to suggest a tool to automate this process. Our end goal is for tool builders to address possible gaps and provide additional aid to data scientists, who can then focus more on their actual work rather than the routine and tedious cleaning duties.