基于软件复杂网络的面向对象软件关键类识别

Jiaming Wang, J. Ai, Yiwen Yang, Wenzhu Su
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引用次数: 15

摘要

识别软件系统中最重要的类对于工程师理解或维护不熟悉的系统至关重要。复杂网络理论为研究大型软件的特性提供了一种新的途径。不幸的是,目前大多数研究只考虑了影响软件结构的一个或有限数量的因素,使得挖掘软件关键类别的结果不准确。因此,我们提出了一种使用各种复杂网络度量来从全局和局部方面自动识别关键类的方法。从全局角度来看,主要考虑类的位置及其对软件信息流的控制能力。从局部方面,我们关注类与相邻类的交互,以及类本身的复杂性。实验在两个java开源项目上进行。结果表明,与现有文献相比,该方法可以准确地识别关键类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying key classes of object-oriented software based on software complex network
Identifying the most important classes in a software system is crucial for engineers to understand or maintain an unfamiliar system. Complex network theory provides a new way to study the characteristics of large-scale software. Unfortunately, most current studies consider only one or a limited number of factors affecting software structure, rendering inaccurate the results of mining the key classes of software. Thus, we propose an approach using various complex network metrics to automatically identify key classes from global and local aspects. From the global aspect, the location of a class and its ability to control the information flow of software are mainly considered. From local aspects, we focus on the interactions of classes with their neighbors, as well as the complexity of the class itself. Experiments are performed on two java open-source projects. Results show that this approach can accurately identify key classes compared with existing literature.
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