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ICSE 2022
Sun 8 - Fri 27 May 2022
Fri 13 May 2022 03:30 - 03:45 at ICSE Demo room 1 - Machine Learning with and for SE Chair(s): Xiaoyuan Xie

Deep learning (DL) models are widely used in software applications. Novel DL models and datasets are published from time to time. Developers may also tempt to apply new software engineering (SE) techniques on their DL models. However, no existing work supports the applications of software testing and debugging techniques on new DL models and their datasets without modifying the code. Developers should manually write code to glue every combination of models, datasets, and SE technique and chain them together.

We propose SEbox4DL, a novel and modular toolbox that automatically integrates models, datasets, and SE techniques into SE pipelines seen in developing DL models. SEbox4DL exemplifies six SE pipelines and can be extended with ease. Each user-defined task in the pipelines is to implement a SE technique within a function with a unified interface so that the whole design of SEbox4DL is generic, modular, and extensible. We have implemented several SE techniques as user-defined tasks to make SEbox4DL off-the-shelf. Our experiments demonstrate that SEbox4DL can simplify the applications of software testing and repair techniques on the latest or popular DL models and datasets. The toolbox is open-source and published at https://github.com/Wsine/SEbox4DL. A video for demonstration is available at: https://youtu.be/EYeFFi4lswc.

Fri 13 May

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03:00 - 04:00
Machine Learning with and for SEDEMO - Demonstrations at ICSE Demo room 1
Chair(s): Xiaoyuan Xie School of Computer Science, Wuhan University, China
HUDD: A tool to debug DNNs for safety analysis
DEMO - Demonstrations
Hazem FAHMY University of Luxembourg, Fabrizio Pastore University of Luxembourg, Lionel Briand University of Luxembourg; University of Ottawa
Pre-print Media Attached
WhyGen: Explaining ML-powered Code Generation by Referring to Training Examples
DEMO - Demonstrations
Weixiang Yan Beijing University of Posts and Telecommunications, Yuanchun Li Microsoft Research
DOI Pre-print Media Attached
SEbox4DL: A Modular Software Engineering Toolbox for Deep Learning Models
DEMO - Demonstrations
Zhengyuan Wei City University of Hong Kong, Hong Kong, Haipeng Wang City University of Hong Kong, Zhen Yang City University of Hong Kong, China, Wing-Kwong Chan City University of Hong Kong, Hong Kong

Information for Participants
Fri 13 May 2022 03:00 - 04:00 at ICSE Demo room 1 - Machine Learning with and for SE Chair(s): Xiaoyuan Xie
Info for room ICSE Demo room 1:

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