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VL/HCC 2020
Tue 11 - Fri 14 August 2020 Dunedin, New Zealand
Thu 13 Aug 2020 08:15 - 08:30 at Zoom Room - Data Science Chair(s): Advait Sarkar

Duplicating one’s own code makes it faster to write software. This expediency is particularly valuable for users of computational notebooks. Duplication allows notebook users to quickly test hypotheses and iterate over data. In this paper, we explore how much, how and from where code duplication occurs in computational notebooks, and identify potential barriers to code reuse. Previous work in the area of computational notebooks describes developers’ motivations for reuse and duplication but does not show how much reuse occurs or which barriers they face when reusing code. To address this gap, we first analyzed GitHub repositories for code duplicates contained in a repository’s Jupyter notebooks, and then conducted an observational user study of code reuse, where participants solved specific tasks using notebooks. Our findings reveal that repositories in our sample have a median self-duplication rate of 5%. However, in our user study, few participants duplicated their own code, preferring to reuse code from online sources.

Thu 13 Aug
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research-papers
08:00 - 08:45: Research Papers - Data Science at Zoom Room
Chair(s): Advait SarkarMicrosoft Research and University of Cambridge
research-papers08:00 - 08:07
Talk
Paula PereiraUniversity of Minho, Jácome CunhaHASLab/INESC TEC & University of Minho, João Paulo FernandesUniversity of Coimbra
Authorizer link Media Attached
research-papers08:08 - 08:15
Talk
Krishna SubramanianRWTH Aachen University, Nur Al-Huda HamdanRWTH Aachen University, Jan BorchersRWTH Aachen University
Authorizer link File Attached
research-papers08:15 - 08:30
Talk
Andreas KoenzenUniversity of Victoria, Neil ErnstUniversity of Victoria, Margaret-Anne StoreyUniversity of Victoria
Authorizer link Pre-print
research-papers08:30 - 08:45
Talk
Sam LauUniversity of California San Diego, Ian DrososUniversity of California San Diego, Julia MarkelUniversity of California San Diego, Philip GuoUniversity of California San Diego
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