You see what I want you to see: poisoning vulnerabilities in neural code search-Reference-Cited by-同舟云学术

You see what I want you to see: poisoning vulnerabilities in neural code search

Published:2022-11-07 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
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Author:

Wan Yao¹,Zhang Shijie¹,Zhang Hongyu²,Sui Yulei³,Xu Guandong³,Yao Dezhong¹,Jin Hai¹,Sun Lichao⁴

Affiliation:

1. Huazhong University of Science and Technology, China

2. University of Newcastle, Australia

3. University of Technology Sydney, Australia

4. Lehigh University, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3540250.3549153

Reference45 articles.

1. 2022. BitBucket. bitbucket.org [Online ; accessed 1- Mar- 2022 ]. 2022. BitBucket. bitbucket.org [Online; accessed 1-Mar-2022].

2. 2022. GitHub. https://www.github.com [Online ; accessed 1- Mar- 2022 ]. 2022. GitHub. https://www.github.com [Online; accessed 1-Mar-2022].

3. Unified Pre-training for Program Understanding and Generation

4. Pavol Bielik and Martin T. Vechev . 2020. Adversarial Robustness for Code . In Proceedings of the 37th International Conference on Machine Learning, ICML 2020 , 13-18 July 2020 , Virtual Event (Proceedings of Machine Learning Research , Vol. 119). PMLR, 896– 907 . Pavol Bielik and Martin T. Vechev. 2020. Adversarial Robustness for Code. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event (Proceedings of Machine Learning Research, Vol. 119). PMLR, 896–907.

5. When deep learning met code search

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