...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>The Journal of Systems and Software >Exploring community structure of software Call Graph and its applications in class cohesion measurement
【24h】

Exploring community structure of software Call Graph and its applications in class cohesion measurement

机译：探索软件Call Graph的社区结构及其在班级凝聚力测量中的应用

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Many complex networked systems exhibit natural divisions of network nodes. Each division, or community, is a densely connected subgroup. Such community structure not only helps comprehension but also finds wide applications in complex systems. Software networks, e.g., Class Dependency Networks, are such networks with community structures, but their characteristics at the function or method call granularity have not been investigated, which are useful for evaluating and improving software intra-dass structure. Moreover, existing proposed applications of software community structure have not been directly compared or combined with existing software engineering practices. Comparison with baseline practices is needed to convince practitioners to adopt the proposed approaches. In this paper, we show that networks formed by software methods and their calls exhibit relatively significant community structures. Based on our findings we propose two new class cohesion metrics to measure the cohesiveness of object-oriented programs. Our experiment on 10 large open-source Java programs validate the existence of community structures and the derived metrics give additional and useful measurement of class cohesion. As an application we show that the new metrics are able to predict software faults more effectively than existing metrics.
机译：许多复杂的联网系统表现出网络节点的自然划分。每个部门或社区都是紧密相连的子组。这种社区结构不仅有助于理解，而且在复杂的系统中得到广泛的应用。软件网络，例如类相关性网络，是具有社区结构的这样的网络，但是尚未研究它们在功能或方法调用粒度方面的特性，这对于评估和改进软件内部结构很有用。而且，尚未将现有的软件社区结构的建议应用程序直接与现有软件工程实践进行比较或结合。需要与基准实践进行比较，以说服从业人员采用建议的方法。在本文中，我们证明了由软件方法形成的网络及其调用表现出相对重要的社区结构。根据我们的发现，我们提出了两个新的类内聚性度量标准来衡量面向对象程序的内聚性。我们在10个大型开源Java程序上的实验验证了社区结构的存在，并且派生的度量标准提供了对类内聚性的附加且有用的度量。作为一个应用程序，我们展示了新指标比现有指标能够更有效地预测软件故障。

著录项

  • 来源
    《The Journal of Systems and Software》 |2015年第10期|193-210|共18页
  • 作者

    Yu Qu; Xiaohong Guan; Qinghua Zheng; Ting Liu; Lidan Wang; Yuqiao Hou; Zijiang Yang;

  • 作者单位

    Ministry of Education Key Lab for Intelligent Network and Network Security, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China;

    Ministry of Education Key Lab for Intelligent Network and Network Security, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China;

    Ministry of Education Key Lab for Intelligent Network and Network Security, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China;

    Ministry of Education Key Lab for Intelligent Network and Network Security, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China;

    Ministry of Education Key Lab for Intelligent Network and Network Security, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China;

    Ministry of Education Key Lab for Intelligent Network and Network Security, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China;

    Department of Computer Science, Western Michigan University, Kalamazoo, MI 48167, USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Class cohesion metrics; Complex network; Community structure;

    机译：类内聚度量;复杂的网络;社区结构;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号