Complex network analysis in Java application systems

Ping-ting SHEN; Liang-yu CHEN

doi:10.3969/j.issn.1000-5641.2017.01.006

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Ping-ting SHEN, Liang-yu CHEN. Complex network analysis in Java application systems[J]. Journal of East China Normal University (Natural Sciences), 2017, (1): 38-51. doi: 10.3969/j.issn.1000-5641.2017.01.006

Citation:

Ping-ting SHEN, Liang-yu CHEN. Complex network analysis in Java application systems[J]. Journal of East China Normal University (Natural Sciences), 2017, (1): 38-51. doi: 10.3969/j.issn.1000-5641.2017.01.006

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Complex network analysis in Java application systems

doi: 10.3969/j.issn.1000-5641.2017.01.006

Ping-ting SHEN,
Liang-yu CHEN^,

Shanghai Key Lab of Trustworthy Computing, East China Normal University, Shanghai 200062, China

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Author Bio:
沈娉婷, 女, 硕士研究生, 研究方向为数据库与数据挖掘. E-mail: spt0726@hotmail.com
Corresponding author: 陈良育, 男, 副教授, 研究方向为符号计算.E-mail: lychen@sei.ecnu.edu.cn
Received Date: 2015-12-29
Publish Date: 2017-01-25

Abstract

Abstract

A lot of empirical studies have demonstrated that Java software system is a kind of artificial complex network and its in-degree distribution obeys the power law, while out-degree distribution is lognormal. However, most experiment objects in these studies are Java development tools, such as JDK, log4j and Tomcat, and the type of data analyzed in dependence graph is limited, because they only consider some class dependence relationships and omit certain useful data types, like member variables and local variables. In this paper, we all useful dependence relationships between entities or modules on both class and function levels, and we further propose a novel method to transform a system network into a weighted directed graph. Comprehensive experiment results show that the in- and out-degree of 10 types of Java application systems mostly fit the power law distributions, and our proposed method to detect the scale-free feature of a weighted and directed network is effective in analyzing Java application systems.
- complex network,
- ava application systems,
- power law distribution,
- class dependence graph,
- function dependence graph

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References(25)

References

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