2018/04/19 by Mary Beth Kery, Marissa Radensky, Mahima Arya +2 · 8 citations
Computer Science · Decision Sciences · #Software Engineering Research #Scientific Computing and Data Management #Advanced Data Storage Technologies
paper · doi:10.1145/3173574.3173748
openalex publication_date 2018/04/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
Literate programming tools are used by millions of programmers today, and are intended to facilitate presenting data analyses in the form of a narrative. We interviewed 21 data scientists to study coding behaviors in a literate programming environment and how data scientists kept track of variants they explored. For participants who tried to keep a detailed history of their experimentation, both informal and formal versioning attempts led to problems, such as reduced notebook readability. During iteration, participants actively curated their notebooks into narratives, although primarily through cell structure rather than markdown explanations. Next, we surveyed 45 data scientists and asked them to envision how they might use their past history in an future version control system. Based on these results, we give design guidance for future literate programming tools, such as providing history search based on how programmers recall their explorations, through contextual details including images and parameters.