Improving the performance of code vulnerability prediction using abstract syntax tree information-Reference-Cited by-同舟云学术

Improving the performance of code vulnerability prediction using abstract syntax tree information

Published:2022-11-07 Issue: Volume: Page:
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Container-title:Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering
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Author:

Al Debeyan Fahad¹,Hall Tracy¹,Bowes David¹

Affiliation:

1. Lancaster University, UK

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3558489.3559066

Reference50 articles.

1. MWMOTE--Majority Weighted Minority Oversampling Technique for Imbalanced Data Set Learning

2. Vulnerability Prediction From Source Code Using Machine Learning

3. Sabri Boughorbel , Fethi Jarray , and Mohammed El-Anbari . 2017. Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric. PLOS ONE, 12, 6 ( 2017 ), 06, 1–17. Sabri Boughorbel, Fethi Jarray, and Mohammed El-Anbari. 2017. Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric. PLOS ONE, 12, 6 (2017), 06, 1–17.

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