软件结构演化及其与子图缺陷的关系

Ana Vrankovic, Tihana Galinac Grbac, Z. Car
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引用次数: 1

摘要

网络分析已成功地应用于软件工程中,以理解软件中的结构效应。系统软件被表示为网络图,网络度量被用来分析系统质量。本研究的动机来自于先前的一项研究,该研究将软件结构表示为三节点子图,并经验地确定了软件结构随着系统发布而不断发展。本文在前人研究的基础上,进一步分析了软件网络图中子图的结构演化与缺陷之间的关系。本研究探讨了子图缺陷在软件演化过程中的行为及其对系统缺陷的影响。统计方法用于研究系统版本和子图类型之间的子图缺陷。作者得出结论,软件版本在平均子图类型缺陷和子图频率分布方面具有相似的行为。然而,不同的子图类型具有不同的缺陷分布。基于这些结论,作者鼓励在缺陷预测和软件建模中使用基于子图的软件表示。这些有希望的发现有助于软件工程规程的进一步发展,并帮助软件开发人员和质量管理人员更好地建模,并在子图表示的代码结构中集中他们的测试工作。
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Software structure evolution and relation to subgraph defectiveness
Network analysis has been successfully applied in software engineering to understand structural effects in the software. System software is represented as a network graph, and network metrics are used to analyse system quality. This study is motivated by a previous study, which represents the software structure as three-node subgraphs and empirically identifies that software structure continuously evolves over system releases. Here, the authors extend the previous study to analyse the relation of structural evolution and the defectiveness of subgraphs in the software network graph. This study investigates the behaviour of subgraph defects through software evolution and their impact on system defectiveness. Statistical methods were used to study subgraph defectiveness across versions of the systems and across subgraph types. The authors conclude that software versions have similar behaviours in terms of average subgraph type defectiveness and subgraph frequency distributions. However, different subgraph types have different defectiveness distributions. Based on these conclusions, the authors motivate the use of subgraph-based software representation in defect predictions and software modelling. These promising findings contribute to the further development of the software engineering discipline and help software developers and quality management in terms of better modelling and focusing their testing efforts within the code structure represented by subgraphs.
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