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2020 IEEE International Conference on Electro Information Technology (EIT) - Scalable Cloud-Based Tool to Empirically Detect Vulnerable Code Patterns in Large-Scale System by Block, Matthew; Barcaskey, Benjamin; Nimmo, Andrew; Alnaeli, Saleh; Gilbert, Ian; Altahat, Zaid is a scholarly article available to read on EtoBox.

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Open-source development is a well-accepted model by software development communities from both academia and industry. Many companies and corporations adopt and use open source systems daily as a core component in their business activities. One of the most important factors that will determine the success of this model is security. The security of software systems is a combination of source code quality, stability, and vulnerabilities. Software vulnerabilities can be introduced by many factors, some of which are the way that programmers write their programs, their background on security standards, and safe programming practices. This paper describes a cloud-based software tool developed by the authors that can help our computing communities in both academia and research to evaluate their software systems on the source code level to help them identify and detect some of the well-known source code vulnerability patterns that can cause security issues if maliciously exploited. The paper also presents an empirical study on the prevalence of vulnerable C/C++ coding patterns inside three large-scale open-source systems comprising more than 42 million lines of source code. The historical d

Author

Block, Matthew; Barcaskey, Benjamin; Nimmo, Andrew; Alnaeli, Saleh; Gilbert, Ian; Altahat, Zaid

Publisher

IEEE

Published

2020

Language

EN