AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities

Many Machine Learning(ML)-based approaches have been proposed to automatically detect, localize, and repair software vulnerabilities. While ML-based methods are more effective than program analysis-based vulnerability analysis tools, few have been integrated into modern Integrated Development Enviro...

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Bibliographic Details
Published in:	Empirical software engineering : an international journal Vol. 29; no. 1; p. 4
Main Authors:	Fu, Michael, Tantithamthavorn, Chakkrit, Le, Trung, Kume, Yuki, Nguyen, Van, Phung, Dinh, Grundy, John
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.02.2024 Springer Nature B.V
Subjects:	C++ (programming language) Classification Compilers Computer Science Cybersecurity Empirical analysis Interpreters Machine learning Mining Software Repositories (MSR) Multiple objective analysis Productivity Programming environments Programming Languages Security aspects Software development Software Engineering/Programming and Operating Systems Software reliability Source code Visual programming languages Vulnerability Vulnerability localization Vulnerability repair Vulnerability classification Vulnerability prediction
ISSN:	1382-3256, 1573-7616
Online Access:	Get full text
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