TY - JOUR
T1 - Ordered Metric Methods of Classes Dependency Graph Based on Structure Entropy
AU - Aihua Gu , Jinxia Xu, Lu Li, Shujun Li, Qifeng Xun, Jian Dong and Zonglin Guo
JO - Journal of Information and Computing Science
VL - 4
SP - 272
EP - 278
PY - 2024
DA - 2024/01
SN - 14
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22403.html
KW - object-oriented class, software quality, structure entropy, complex networks, software metrics 

AB - 1 School of Information Engineering, Yancheng Teachers University, Yancheng 224002, China 
2 Department of Medical Instrumen,Yancheng Third People’s Hospital, Yancheng 224001, China 
(Received August 01 2019, accepted September 26 2019) 
In this paper, structure entropy which is based on classes dependency graph of a software system 
is  proposed  to measure  the  complexity  of  the  system.  In  order  to  research  the  structure entropy  metrics  of 
classes dependency graph in some  large  software systems, this paper takes the first  step to mathematically 
prove that structure entropy does not have the property of cohesion. Thus, a structure entropy can be used as a 
single  metric  of  complexity.  And  then,  a  program  is  written  based  on  relevant  matrix  algorithm  with  the 
construction of classes dependency graph. The corresponding metrics of structure entropy of three pieces of 
open source software are calculated and figured out based on classes dependency graph. The calculation shows 
that most classes in the  three pieces of the open source software  are  of randomness. Meanwhile, values of 
structure entropy features complex network Scale-free. Therefore, the different values of the structure entropy 
of open source software classes dependency graph influences the evaluation of software quality. Furthermore, 
some complex network statistical characteristics are found out in this paper, which will facilitate the further 
research on structure entropy as a metric of software complexity for sophisticated networks.