Enabling automatic repair of source code vulnerabilities using data-driven methods-Reference-Cited by-同舟云学术

Enabling automatic repair of source code vulnerabilities using data-driven methods

Published:2022-05-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM/IEEE 44th International Conference on Software Engineering: Companion Proceedings
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Author:

Grishina Anastasiia¹

Affiliation:

1. Simula Research Laboratory, Oslo, Norway

Funder

Research Council of Norway

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3510454.3517063

Reference35 articles.

1. B. OpenMind . The 5 Most Infamous Software Bugs in History. https://www.bbvaopenmind.com/en/technology/innovation/the-5-most-infamous-software-bugs-in-history/ . 2015 . B. OpenMind. The 5 Most Infamous Software Bugs in History. https://www.bbvaopenmind.com/en/technology/innovation/the-5-most-infamous-software-bugs-in-history/. 2015.

2. A. Wilson , R. Schulman , K. Bankston , and T. Herr . Bugs in the System: A Primer on the Software Vulnerability Ecosystem and Its Policy Implications. Tech. rep. New America , Open Technology Institute (OTI) , 2016 . A. Wilson, R. Schulman, K. Bankston, and T. Herr. Bugs in the System: A Primer on the Software Vulnerability Ecosystem and Its Policy Implications. Tech. rep. New America, Open Technology Institute (OTI), 2016.

3. Automatic Software Repair

4. A Survey of Machine Learning for Big Code and Naturalness

5. A Survey of Test Based Automatic Program Repair

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