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MSR 2022
Mon 23 - Tue 24 May 2022
co-located with ICSE 2022

In recent years, Jupyter notebooks have grown in popularity in several domains of software engineering, such as data science, machine learning, and computer science education. Their popularity has to do with their rich features for presenting and visualizing data, however, recent studies show that notebooks also share a lot of drawbacks: high number of code clones, low reproducibility, etc.

In this work, we carry out a comparison between Python code written in Jupyter Notebooks and in traditional Python scripts. We compare the code from two perspectives: structural and stylistic. In the first part of the analysis, we report the difference in the number of lines, the usage of functions, as well as various complexity metrics. In the second part, we show the difference in the number of stylistic issues and provide an extensive overview of the 15 most frequent stylistic issues in the studied mediums. Overall, we demonstrate that notebooks are characterized by the lower code complexity, however, their code could be perceived as more entangled than in the scripts. As for the style, notebooks tend to have 1.4 times more stylistic issues, but at the same time, some of them are caused by specific coding practices in notebooks and should be considered as false positives. With this research, we want to pave the way to studying specific problems of notebooks that should be addressed by the development of notebook-specific tools, and provide various insights that can be useful in this regard.

Thu 19 May

Displayed time zone: Eastern Time (US & Canada) change

03:00 - 03:50
Session 8: Large-Scale Mining & Software EcosystemsTechnical Papers / Data and Tool Showcase Track at MSR Main room - odd hours
Chair(s): Fiorella Zampetti University of Sannio, Italy, Gregorio Robles Universidad Rey Juan Carlos
03:00
7m
Talk
An Empirical Study on the Survival Rate of GitHub Projects
Technical Papers
Adem Ait-Fonolla IN3 - UOC, Javier Luis Cánovas Izquierdo IN3 - UOC, Jordi Cabot Open University of Catalonia, Spain
Pre-print
03:07
7m
Talk
A Large-Scale Comparison of Python Code in Jupyter Notebooks and ScriptsDistinguished Paper Award
Technical Papers
Konstantin Grotov JetBrains Research, ITMO University, Sergey Titov JetBrains Research, Vladimir Sotnikov JetBrains Research, Yaroslav Golubev JetBrains Research, Timofey Bryksin JetBrains Research; HSE University
DOI Pre-print
03:14
7m
Talk
Do Customized Android Frameworks Keep Pace with Android?
Technical Papers
Pei Liu Monash University, Mattia Fazzini University of Minnesota, John Grundy Monash University, Li Li Monash University
03:21
4m
Talk
Lupa: A Platform for Large Scale Analysis of The Progamming Language Usage
Data and Tool Showcase Track
Anna Vlasova JetBrains Research, Maria Tigina JetBrains Research, ITMO University, Ilya Vlasov Saint Petersburg State University, Anastasia Birillo JetBrains Research, Yaroslav Golubev JetBrains Research, Timofey Bryksin JetBrains Research; HSE University
DOI Pre-print
03:25
4m
Talk
GitDelver Enterprise Dataset (GDED): An Industrial Closed-source Dataset for Socio-Technical Research
Data and Tool Showcase Track
Nicolas Riquet University of Namur, Xavier Devroey University of Namur, Benoît Vanderose University of Namur
Pre-print
03:29
4m
Talk
DaSEA – A Dataset for Software Ecosystem Analysis
Data and Tool Showcase Track
Petya Buchkova IT University of Copenhagen, Joakim Hey Hinnerskov IT University of Copenhagen, Kasper Olsen IT University of Copenhagen, Rolf-Helge Pfeiffer IT University of Copenhagen
Pre-print Media Attached
03:33
4m
Talk
Dataset: Dependency Networks of Open Source Libraries Available Through CocoaPods, Carthage and Swift PM
Data and Tool Showcase Track
Kristiina Rahkema University of Tartu, Dietmar Pfahl University of Tartu
Pre-print Media Attached
03:37
13m
Live Q&A
Discussions and Q&A
Technical Papers


Information for Participants