Can requirements dependency network be used as early indicator of software integration bugs?

Junjie Wang, Juan Li, Qing Wang, D. Yang, He Zhang, Mingshu Li
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引用次数: 10

Abstract

Complexity cohesion and coupling have been recognized as prominent indicators for software quality. One characterization of software complexity is the existence of dependency relationship. Moreover, degree of dependency reflects the cohesion and coupling between software elements. Dependencies on design and implementation phase have been proven as important predictors for software bugs. We empirically investigated how requirements dependencies correlate with and predict software integration bugs, which can provide early estimate regarding software quality, therefore facilitate decision making early in the software lifecycle. We conducted network analysis on requirements dependency networks of two commercial software projects. We then performed correlation analysis between network measures (e.g., degree, closeness) and number of bugs. Afterwards, bug prediction models were built using these network measures. Significant correlation is observed between most of our network measures and number of bugs. These network measures can predict the number of bugs with high accuracy and sensitivity. We further identified the significant predictors for bug prediction. Besides, the indication effect of network measures on bug number varies among different types of requirements dependency. These observations show that requirements dependency network can be used as an early indicator of software Integration bugs.
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需求依赖网络可以用作软件集成缺陷的早期指示器吗?
复杂性、内聚和耦合被认为是软件质量的重要指标。软件复杂性的一个特征是依赖关系的存在。此外,依赖程度反映了软件元素之间的内聚和耦合。设计和实现阶段的依赖性已被证明是软件bug的重要预测因素。我们根据经验调查了需求依赖关系是如何与软件集成错误相关联并预测的,这可以提供关于软件质量的早期评估,从而促进软件生命周期早期的决策制定。我们对两个商业软件项目的需求依赖网络进行了网络分析。然后,我们对网络度量(例如,程度、接近程度)和漏洞数量进行相关性分析。然后,利用这些网络度量建立bug预测模型。在我们的大多数网络测量和bug数量之间可以观察到显著的相关性。这些网络测量方法能够准确、灵敏地预测漏洞数量。我们进一步确定了bug预测的重要预测因子。此外,网络度量对bug数量的指示作用在不同类型的需求依赖中是不同的。这些观察表明需求依赖网络可以用作软件集成缺陷的早期指示器。
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