Interactions for Untangling Messy History in a Computational Notebook

Experimentation through code is central to data scientists' work. Prior work has identified the need for interaction techniques for quickly exploring multiple versions of the code and the associated outputs. Yet previous approaches that provide history information have been challenging to scale: real use produces a high number of versions of different code and non-code artifacts with dependency relationships and a convoluted mix of different analysis intents. Prior work has found that navigating these records to pick out the relevant information for a given task is difficult and time consuming. We introduce Verdant, a new system with a novel versioning model to support fast retrieval and sensemaking of messy version data. Verdant provides light-weight interactions for comparing, replaying, and tracing relationships among many versions of different code and non-code artifacts in the editor. We implemented Verdant into Jupyter Notebooks, and validated the usability of Verdant's interactions through a usability study.