Skip to main content

Research Repository

Advanced Search

Security feature measurement for frequent dynamic execution paths in software system

Wang, Qian; Ren, Jiadong; Yang, Xiaoli; Cheng, Yongqiang; Davis, Darryl N.; Hu, Changzhen


Qian Wang

Jiadong Ren

Xiaoli Yang

Yongqiang Cheng

Darryl N. Davis

Changzhen Hu


© 2018 Qian Wang et al. The scale and complexity of software systems are constantly increasing, imposing new challenges for software fault location and daily maintenance. In this paper, the Security Feature measurement algorithm of Frequent dynamic execution Paths in Software, SFFPS, is proposed to provide a basis for improving the security and reliability of software. First, the dynamic execution of a complex software system is mapped onto a complex network model and sequence model. This, combined with the invocation and dependency relationships between function nodes, fault cumulative effect, and spread effect, can be analyzed. The function node security features of the software complex network are defined and measured according to the degree distribution and global step attenuation factor. Finally, frequent software execution paths are mined and weighted, and security metrics of the frequent paths are obtained and sorted. The experimental results show that SFFPS has good time performance and scalability, and the security features of the important paths in the software can be effectively measured. This study provides a guide for the research of defect propagation, software reliability, and software integration testing.


Wang, Q., Ren, J., Yang, X., Cheng, Y., Davis, D. N., & Hu, C. (2018). Security feature measurement for frequent dynamic execution paths in software system. Security and communication networks, 2018, 1-10.

Journal Article Type Article
Acceptance Date Feb 19, 2018
Online Publication Date Mar 22, 2018
Publication Date Mar 22, 2018
Deposit Date Mar 23, 2018
Publicly Available Date Mar 26, 2018
Journal Security and Communication Networks
Print ISSN 1939-0114
Electronic ISSN 1939-0122
Publisher Hindawi
Peer Reviewed Peer Reviewed
Volume 2018
Article Number 5716878
Pages 1-10
Keywords Computer Networks and Communications; Information Systems
Public URL
Publisher URL


Article (1.7 Mb)

Copyright Statement
© 2018 Qian Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

You might also like

Downloadable Citations