GitHub Considered Harmful? Analyzing Open-Source Projects for the Automatic Generation of Cryptographic API Call Sequences-Reference-Cited by-同舟云学术

GitHub Considered Harmful? Analyzing Open-Source Projects for the Automatic Generation of Cryptographic API Call Sequences

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS)
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Author:

Tony Catherine¹,Díaz Ferreyra Nicolás E.¹,Scandariato Riccardo¹

Affiliation:

1. Hamburg University of Technology,Institute of Software Security,Hamburg,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10061851/10061812/10062390.pdf?arnumber=10062390

Reference25 articles.

1. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

2. Asleep at the Keyboard? Assessing the Security of GitHub Copilot’s Code Contributions;pearce;43rd IEEE Symposium on Security and Privacy SP,2022

3. Negative Results on Mining Crypto-API Usage Rules in Android Apps

4. BLEU: A Method for Automatic Evaluation of Machine Translation;papineni;Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL '02,2002

5. Evaluating Large Language Models Trained on Code;chen;CoRR,2021

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