1. A Novel Algorithm for Identifying Key Function Nodes in Software Network Based on Evidence Theory
- Author
-
Jun Dong, Jiadong Ren, Xiaolin Zhao, Jiaxin Liu, Qian Wang, and Shan Chun
- Subjects
Software network ,Computer Networks and Communications ,Computer science ,media_common.quotation_subject ,02 engineering and technology ,Complex network ,computer.software_genre ,01 natural sciences ,Computer Graphics and Computer-Aided Design ,010305 fluids & plasmas ,Software fault detection ,Artificial Intelligence ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Key (cryptography) ,020201 artificial intelligence & image processing ,Data mining ,Function (engineering) ,computer ,Software ,media_common - Abstract
In a software network system, it is of great significance to identify key functions for software fault detection and maintenance. In order to better understand the characteristics and internal structure of software, a key Node Discovery algorithm based on Evidence Theory called NDET is proposed in this paper. First, the software complex network model is constructed according to the execution process of the software. Based on the Dempster-Shafer evidence theory (D-S evidence theory), the discernment frame is formed, the maximum and minimum values of the network degree and strength are determined. Second, the Basic Probability Assignment (BPA) of each node degree is calculated by considering the node degree distribution ratio value. Third, based on Dempster’s rule of combination, the evidential centrality of the node itself and the fluctuation value of the node influenced by neighbor nodes are considered for the key measurement. Finally, by using the Susceptible–Infected–Recovered (SIR) model to simulate the spreading process on real software networks, the performance of NDET is evaluated. Experiment results verify the validity and accuracy of NDET for identifying key function nodes in software.
- Published
- 2019