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An Empirical Study of Social Networks Metrics in Object-Oriented Software

机译:面向对象软件中社交网络指标的实证研究

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We study the application to object-oriented software of new metrics, derived from SocialNetwork Analysis. Social Networks metrics, as for instance, the EGO metrics, allow to identifythe role of each single node in the information flow through the network, being related tosoftware modules and their dependencies. These metrics are compared with other traditionalsoftware metrics, like the Chidamber-Kemerer suite, and software graph metrics. We examine the empirical distributions of all the metrics, bugs included, across the softwaremodules of several releases of two large Java systems, Eclipse and Netbeans. We provide analyticaldistribution functions suitable for describing and studying the observed distributions. We study also correlations among metrics and bugs. We found that the empirical distributions systematically show fat-tails for all the metrics. Moreover, the various metric distributions look very similar and consistent across all systemreleases and are also very similar in both the studied systems. These features appear to betypical properties of these software metrics.
机译:我们研究了源自SocialNetwork Analysis的新指标在面向对象软件中的应用。社交网络度量标准(例如EGO度量标准)允许识别与软件模块及其依赖性相关的每个单个节点在通过网络的信息流中的角色。将这些指标与其他传统软件指标(如Chidamber-Kemerer套件)和软件图指标进行比较。我们检查了跨两个大型Java系统的几个发行版(Eclipse和Netbeans)的软件模块的所有度量(包括错误)的经验分布。我们提供适合描述和研究观察到的分布的分析分布函数。我们还将研究指标和错误之间的相关性。我们发现,经验分布系统地显示了所有指标的尾巴。此外,在所有系统版本中,各种度量分布看起来非常相似且一致,并且在两个研究的系统中也非常相似。这些功能似乎是这些软件指标的典型属性。

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