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MSR 2021
Mon 17 - Wed 19 May 2021
co-located with ICSE 2021

This program is tentative and subject to change.

Tue 18 May 2021 10:33 - 10:41 at MSR Room 2 - ML and Deep Learning

Computational notebooks have become the tool of choice for many data scientists and practitioners for performing analyses and disseminating results. Despite their increasing popularity, the research community cannot yet count on a large, curated dataset of computational notebooks. In this paper, we fill this gap by introducing KGTorrent, a dataset of Python Jupyter notebooks with rich metadata retrieved from Kaggle, a platform hosting data science competitions for learners and practitioners with any levels of expertise. We describe how we built KGTorrent, and provide instructions on how to use it and refresh the collection to keep it up to date. Our vision is that the research community will use KGTorrent to study how data scientists, especially practitioners, use Jupyter Notebook in the wild and identify potential shortcomings to inform the design of its future extensions.

This program is tentative and subject to change.

Tue 18 May
Times are displayed in time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

10:00 - 10:50
10:00
8m
Talk
Fast and Memory-Efficient Neural Code Completion
Technical Papers
Alexey SvyatkovskiyMicrosoft, Sebastian LeeUniversity of Oxford, Anna HadjitofiAlan Turing Institute, Maik RiechertMicrosoft Research, Juliana Vicente FrancoMicrosoft Research, Miltiadis AllamanisMicrosoft Research, UK
Pre-print
10:08
8m
Research paper
Comparative Study of Feature Reduction Techniques in Software Change Prediction
Technical Papers
Ruchika MalhotraDelhi Technological University, Ritvik KapoorDelhi Technological University, Deepti AggarwalDelhi Technological University, Priya GargDelhi Technological University
Pre-print
10:16
8m
Talk
An Empirical Study on the Usage of BERT Models for Code Completion
Technical Papers
Matteo CiniselliUniversità della Svizzera Italiana, Nathan CooperWilliam & Mary, Luca PascarellaUniversità della Svizzera italiana, Denys PoshyvanykCollege of William & Mary, Massimiliano Di PentaUniversity of Sannio, Italy, Gabriele BavotaSoftware Institute, USI Università della Svizzera italiana
Pre-print
10:25
8m
Talk
ManyTypes4Py: A benchmark Python dataset for machine learning-based type inference
Data Showcase
Amir MirDelft University of Technology, Evaldas LatoskinasDelft University of Technology, Georgios GousiosFacebook & Delft University of Technology
10:33
8m
Talk
KGTorrent: A Dataset of Python Jupyter Notebooks from Kaggle
Data Showcase
Luigi QuarantaUniversity of Bari, Italy, Fabio CalefatoUniversity of Bari, Filippo LanubileUniversity of Bari
10:41
8m
Talk
Exploring the relationship between performance metrics and cost saving potential of defect prediction models
Registered Reports
Steffen HerboldUniversity of Göttingen
Pre-print