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ICSE 2022
Sun 8 - Fri 27 May 2022
Tue 10 May 2022 12:15 - 12:20 at ICSE room 1-even hours - Machine Learning with and for SE 9 Chair(s): Baishakhi Ray
Tue 10 May 2022 21:20 - 21:25 at ICSE room 3-odd hours - Machine Learning with and for SE 6 Chair(s): Ali Ouni

Dynamic languages, such as Python and Javascript, trade static typing for developer flexibility and productivity. Lack of static typing can cause run-time exceptions and is a major factor for weak IDE support. To alleviate these issues, PEP 484 introduced optional type annotations for Python. As retrofitting types to existing codebases is error-prone and laborious, machine learning (ML)-based approaches have been proposed to enable automatic type inference based on existing, partially annotated codebases. However, previous ML-based approaches are trained and evaluated on human-provided type annotations, which might not always be sound, and hence this may limit the practicality for real-world usage. In this paper, we present Type4Py, a deep similarity learning-based hierarchical neural network model. It learns to discriminate between similar and dissimilar types in a high-dimensional space, which results in clusters of types. Likely types for arguments, variables, and return values can then be inferred through the nearest neighbor search. Unlike previous work, we trained and evaluated our model on a \emph{type-checked} dataset and used mean reciprocal rank (MRR) to reflect the performance perceived by users. The obtained results show that Type4Py achieves an MRR of 77.1%, which is a substantial improvement of 8.1% and 16.7% over the state-of-the-art approaches Typilus and TypeWriter, respectively. Finally, to aid developers with retrofitting types, we released a Visual Studio Code extension, which uses Type4Py to provide ML-based type auto-completion for Python.

Tue 10 May

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12:00 - 13:00
Machine Learning with and for SE 9Technical Track / SEIP - Software Engineering in Practice / Journal-First Papers at ICSE room 1-even hours
Chair(s): Baishakhi Ray Columbia University
12:00
5m
Talk
Journal First: On the Value of Oversampling for Deep Learning in Software Defect Prediction
Journal-First Papers
Rahul Yedida North Carolina State University, Tim Menzies North Carolina State University
Media Attached
12:05
5m
Talk
Strategies for Reuse and Sharing among Data Scientists in Software Teams
SEIP - Software Engineering in Practice
Will Epperson Carnegie Mellon University, April Wang University of Michigan, Robert DeLine Microsoft Research, Steven M. Drucker Microsoft Research
Pre-print Media Attached
12:10
5m
Talk
What Do They Capture? - A Structural Analysis of Pre-Trained Language Models for Source Code
Technical Track
Yao Wan Huazhong University of Science and Technology, Wei Zhao Huazhong University of Science and Technology, Hongyu Zhang University of Newcastle, Yulei Sui University of Technology Sydney, Guandong Xu University of Technology, Sydney, Hai Jin Huazhong University of Science and Technology
Pre-print Media Attached
12:15
5m
Talk
Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python
Technical Track
Amir Mir Delft University of Technology, Evaldas Latoskinas Delft University of Technology, Sebastian Proksch Delft University of Technology, Netherlands, Georgios Gousios Endor Labs & Delft University of Technology
DOI Pre-print Media Attached
12:20
5m
Talk
Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules
Technical Track
Rangeet Pan Iowa State University, USA, Hridesh Rajan Iowa State University
Pre-print Media Attached
21:00 - 22:00
Machine Learning with and for SE 6Technical Track at ICSE room 3-odd hours
Chair(s): Ali Ouni ETS Montreal, University of Quebec
21:00
5m
Talk
DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs
Technical Track
Jialun Cao Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Meiziniu LI Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Xiao Chen Huazhong University of Science and Technology, Ming Wen Huazhong University of Science and Technology, Yongqiang Tian University of Waterloo, Bo Wu MIT-IBM Watson AI Lab in Cambridge, Shing-Chi Cheung Hong Kong University of Science and Technology
DOI Pre-print Media Attached
21:05
5m
Talk
Fast Changeset-based Bug Localization with BERT
Technical Track
Agnieszka Ciborowska Virginia Commonwealth University, Kostadin Damevski Virginia Commonwealth University
Pre-print Media Attached
21:10
5m
Talk
Multilingual training for Software Engineering
Technical Track
Toufique Ahmed University of California at Davis, Prem Devanbu Department of Computer Science, University of California, Davis
DOI Pre-print Media Attached
21:15
5m
Talk
NeuronFair: Interpretable White-Box Fairness Testing through Biased Neuron Identification
Technical Track
haibin zheng Zhejiang University of Technology, Zhiqing Chen Zhejiang University of Technology, Tianyu Du Zhejiang University, Xuhong Zhang Zhejiang University, Yao Cheng Huawei International, Shouling Ji Zhejiang University, Jingyi Wang Zhejiang University, Yue Yu College of Computer, National University of Defense Technology, Changsha 410073, China, Jinyin Chen College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
DOI Pre-print Media Attached
21:20
5m
Talk
Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python
Technical Track
Amir Mir Delft University of Technology, Evaldas Latoskinas Delft University of Technology, Sebastian Proksch Delft University of Technology, Netherlands, Georgios Gousios Endor Labs & Delft University of Technology
DOI Pre-print Media Attached
21:25
5m
Talk
Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules
Technical Track
Rangeet Pan Iowa State University, USA, Hridesh Rajan Iowa State University
Pre-print Media Attached

Information for Participants
Tue 10 May 2022 12:00 - 13:00 at ICSE room 1-even hours - Machine Learning with and for SE 9 Chair(s): Baishakhi Ray
Info for room ICSE room 1-even hours:

Click here to go to the room on Midspace

Tue 10 May 2022 21:00 - 22:00 at ICSE room 3-odd hours - Machine Learning with and for SE 6 Chair(s): Ali Ouni
Info for room ICSE room 3-odd hours:

Click here to go to the room on Midspace