TensorJSFuzz: Effective Testing of Web-Based Deep Learning Frameworks via Input-Constraint Extraction.
Lili Quan|Xiaofei Xie|Qianyu Guo|Lingxiao Jiang|Sen Chen|Junjie Wang|Xiaohong Li
| Anthology ID: | DBLP:conf/www/QuanXGJ00025 |
|---|---|
| Volume: | Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025 |
| Year: | 2025 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 3405-3414 |
| URL: | https://doi.org/10.1145/3696410.3714649 |
| DOI: | https://doi.org/10.1145/3696410.3714649 |
| DBLP: | conf/www/QuanXGJ00025 |
| BibTeX: |
@inproceedings{quan-2025-tensorjsfuzz,
author = {Lili Quan and
Xiaofei Xie and
Qianyu Guo and
Lingxiao Jiang and
Sen Chen and
Junjie Wang and
Xiaohong Li},
editor = {Guodong Long and
Michale Blumestein and
Yi Chang and
Liane Lewin-Eytan and
Zi Huang and
Elad Yom-Tov},
title = {{TensorJSFuzz: Effective Testing of Web-Based Deep Learning Frameworks via Input-Constraint Extraction}},
booktitle = {{Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025- 2 May 2025}},
pages = {3405--3414},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3696410.3714649},
doi = {https://doi.org/10.1145/3696410.3714649}
}