Building UML class diagram maintainability prediction models based on early metrics
Building UML class diagram maintainability prediction models based on early metrics
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DOI：
10.1109/metric.2003.1232473
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发表时间：
2003-09
期刊：
影响因子：
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通讯作者：
M. Genero;M. Piattini;E. Manso;G. Cantone
中科院分区：
文献类型：
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作者：
M. Genero;M. Piattini;E. Manso;G. Cantone
在面向对象 (OO) 软件的分析和设计中使用度量可以帮助设计人员做出更好的决策，这一事实在软件度量领域越来越重要。此外，基于早期指标的外部质量属性（例如可维护性）的早期指标的必要性越来越大。除此之外，目的是展示如何将测量内部属性（例如 UML 类图的结构复杂性和大小）的早期度量用作早期类图可维护性指标。为此，我们提出了一项对照实验及其复制，我们进行该实验是为了收集经验数据，这反过来又是当前研究的基础。从获得的结果来看，似乎有合理的机会可以基于早期指标构建有用的类图可维护性模型。尽管如此，仍需要更多的实证研究，特别是使用在工业环境中执行的实际项目中获取的数据，以获得全面的知识和经验。
The fact that the usage of metrics in the analysis and design of object oriented (OO) software can help designers make better decisions is gaining relevance in software measurement arena. Moreover, the necessity of having early indicators of external quality attributes, such as maintainability, based on early metrics is growing. In addition to this, the aim is to show how early metrics which measure internal attributes, such as structural complexity and size of UML class diagrams, can be used as early class diagram maintainability indicators. For this purpose, we present a controlled experiment and its replication, which we carried out to gather the empirical data, which in turn is the basis of the current study. From the results obtained, it seems that there is a reasonable chance that useful class diagram maintainability models could be built based on early metrics. Despite this fact, more empirical studies, especially using data taken form real projects performed in industrial settings, are needed in order to obtain a comprehensive body of knowledge and experience.