Towards Understanding the Faults of JavaScript-Based Deep Learning Systems-Reference-Cited by-同舟云学术

Towards Understanding the Faults of JavaScript-Based Deep Learning Systems

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering
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Author:

Quan Lili¹^ORCID,Guo Qianyu²^ORCID,Xie Xiaofei³,Chen Sen¹,Li Xiaohong¹,Liu Yang⁴

Affiliation:

1. Tianjin University, China

2. Zhongguancun Laboratory, China

3. Singapore Management University, Singapore

4. Nanyang Technological University, Singapore

Funder

National Natural Science Foundation of China

the Ministry of Education, Singapore under its Academic Research Fund Tier 1

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3551349.3560427

Reference87 articles.

1. 2022. Keras: The Python Deep Learning Library. https://keras.io 2022. Keras: The Python Deep Learning Library. https://keras.io

2. 2022. ML5.js. https://learn.ml5js.org 2022. ML5.js. https://learn.ml5js.org

3. 2022. Website of this study. https://sites.google.com/view/dl-fault-study4js 2022. Website of this study. https://sites.google.com/view/dl-fault-study4js

4. Martín Abadi , Paul Barham , Jianmin Chen , Zhifeng Chen , Andy Davis , Jeffrey Dean , Matthieu Devin , Sanjay Ghemawat , Geoffrey Irving , Michael Isard , Manjunath Kudlur , Josh Levenberg , Rajat Monga , Sherry Moore , Derek Gordon Murray , Benoit Steiner , Paul A. Tucker , Vijay Vasudevan , Pete Warden , Martin Wicke , Yuan Yu , and Xiaoqiang Zheng . 2016 . TensorFlow: A System for Large-Scale Machine Learning . In Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation, OSDI. USENIX Association, 265–283 . Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek Gordon Murray, Benoit Steiner, Paul A. Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng. 2016. TensorFlow: A System for Large-Scale Machine Learning. In Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation, OSDI. USENIX Association, 265–283.

5. MUBench

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