Empirical studies on the impact of filter‐based ranking feature selection on security vulnerability prediction-Reference-Cited by-同舟云学术

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Empirical studies on the impact of filter‐based ranking feature selection on security vulnerability prediction

Published:2020-12-09 Issue:1 Volume:15 Page:75-89
ISSN:1751-8806
Container-title:IET Software
language:en
Short-container-title:IET softw.

Author:

Chen Xiang¹²,Yuan Zhidan¹,Cui Zhanqi³,Zhang Dun¹,Ju Xiaolin¹

Affiliation:

1. School of Information Science and Technology Nantong University Nantong China

2. Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China

3. Computer School Beijing Information Science and Technology University Beijing China

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Graphics and Computer-Aided Design

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/sfw2.12006

Reference50 articles.

1. Software security testing

2. Software Vulnerability Analysis and Discovery Using Machine-Learning and Data-Mining Techniques

3. A Systematic Literature Review on Fault Prediction Performance in Software Engineering

4. Defect prediction: Accomplishments and future challenges;Kamei Y.;Proc. Int. Conf. Software Anal. Evol. Reengine,2016

5. Walden J. Stuckman J. Scandariato R.: Predicting vulnerable components: Software metrics vs text mining. In: Proceedings of international symposium on software reliability engineering) pp. 23–33. (2014)

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