TY - JOUR
T1 - Analysis on Influential Functions in the Weighted Software Network
AU - He, Haitao
AU - Shan, Chun
AU - Tian, Xiangmin
AU - Wei, Yalei
AU - Huang, Guoyan
N1 - Publisher Copyright:
© 2018 Haitao He et al.
PY - 2018
Y1 - 2018
N2 - Identifying influential nodes is important for software in terms of understanding the design patterns and controlling the development and the maintenance process. However, there are no efficient methods to discover them so far. Based on the invoking dependency relationships between the nodes, this paper proposes a novel approach to define the node importance for mining the influential software nodes. First, according to the multiple execution information, we construct a weighted software network (WSN) to denote the software execution dependency structure. Second, considering the invoking times and outdegree about software nodes, we improve the method PageRank and put forward the targeted algorithm FunctionRank to evaluate the node importance (NI) in weighted software network. It has higher influence when the node has lager value of NI. Finally, comparing the NI of nodes, we can obtain the most influential nodes in the software network. In addition, the experimental results show that the proposed approach has good performance in identifying the influential nodes.
AB - Identifying influential nodes is important for software in terms of understanding the design patterns and controlling the development and the maintenance process. However, there are no efficient methods to discover them so far. Based on the invoking dependency relationships between the nodes, this paper proposes a novel approach to define the node importance for mining the influential software nodes. First, according to the multiple execution information, we construct a weighted software network (WSN) to denote the software execution dependency structure. Second, considering the invoking times and outdegree about software nodes, we improve the method PageRank and put forward the targeted algorithm FunctionRank to evaluate the node importance (NI) in weighted software network. It has higher influence when the node has lager value of NI. Finally, comparing the NI of nodes, we can obtain the most influential nodes in the software network. In addition, the experimental results show that the proposed approach has good performance in identifying the influential nodes.
UR - http://www.scopus.com/inward/record.url?scp=85045728192&partnerID=8YFLogxK
U2 - 10.1155/2018/1525186
DO - 10.1155/2018/1525186
M3 - Article
AN - SCOPUS:85045728192
SN - 1939-0114
VL - 2018
JO - Security and Communication Networks
JF - Security and Communication Networks
M1 - 1525186
ER -
