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MSR 2021
Mon 17 - Wed 19 May 2021
co-located with ICSE 2021
Tue 18 May 2021 10:19 - 10:22 at MSR Room 2 - ML and Deep Learning Chair(s): Hongyu Zhang

Performance metrics are a core component of the evaluation of any machine learning model and used to compare models and estimate their usefulness. Recent work started to question the validity of many performance metrics for this purpose in the context of software defect prediction. Within this study, we explore the relationship between performance metrics and the cost saving potential of defect prediction models. We study whether metrics are suitable proxies to evaluate the cost saving capabilities and derive a theory for the relationship between performance metrics and cost saving potential.

Tue 18 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

10:00 - 10:50
ML and Deep LearningTechnical Papers / Data Showcase / Registered Reports at MSR Room 2
Chair(s): Hongyu Zhang The University of Newcastle
10:01
4m
Talk
Fast and Memory-Efficient Neural Code Completion
Technical Papers
Alexey Svyatkovskiy Microsoft, Sebastian Lee University of Oxford, Anna Hadjitofi Alan Turing Institute, Maik Riechert Microsoft Research, Juliana Franco Microsoft Research, Miltiadis Allamanis Microsoft Research, UK
Pre-print Media Attached
10:05
4m
Research paper
Comparative Study of Feature Reduction Techniques in Software Change Prediction
Technical Papers
Ruchika Malhotra Delhi Technological University, Ritvik Kapoor Delhi Technological University, Deepti Aggarwal Delhi Technological University, Priya Garg Delhi Technological University
Pre-print
10:09
4m
Talk
An Empirical Study on the Usage of BERT Models for Code Completion
Technical Papers
Matteo Ciniselli Università della Svizzera Italiana, Nathan Cooper William & Mary, Luca Pascarella Delft University of Technology, Denys Poshyvanyk College of William & Mary, Massimiliano Di Penta University of Sannio, Italy, Gabriele Bavota Software Institute, USI Università della Svizzera italiana
Pre-print
10:13
3m
Talk
ManyTypes4Py: A benchmark Python dataset for machine learning-based type inference
Data Showcase
Amir Mir Delft University of Technology, Evaldas Latoskinas Delft University of Technology, Georgios Gousios Facebook & Delft University of Technology
Pre-print
10:16
3m
Talk
KGTorrent: A Dataset of Python Jupyter Notebooks from Kaggle
Data Showcase
Luigi Quaranta University of Bari, Italy, Fabio Calefato University of Bari, Filippo Lanubile University of Bari
10:19
3m
Talk
Exploring the relationship between performance metrics and cost saving potential of defect prediction models
Registered Reports
Steffen Herbold University of Göttingen
Pre-print
10:22
28m
Live Q&A
Discussions and Q&A
Technical Papers


Information for Participants
Tue 18 May 2021 10:00 - 10:50 at MSR Room 2 - ML and Deep Learning Chair(s): Hongyu Zhang
Info for room MSR Room 2:

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