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首页> 外文期刊>Arabian Journal for Science and Engineering >Theoretical and Empirical Validation of Coupling Metrics for Object-Oriented DataWarehouse Design
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Theoretical and Empirical Validation of Coupling Metrics for Object-Oriented DataWarehouse Design

机译：面向对象数据仓库设计耦合度量的理论和经验验证

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The conceptual model of a data warehouse can be used to determine its quality during the early stages of design. Metrics have been proposed in the past to quantify the structural complexity of these models. A majority of these metrics focus on the internal quality attributes of size and complexity. Unfortunately, not many measures have been proposed to assess the magnitude of coupling in the data warehouse multidimensional models. Coupling has a significant impact on the complexity and, in turn, quality of these models. In our previous work, we had put forward measures to determine the scope of inheritance and aggregation coupling between classes present in the object-oriented conceptual model of the data warehouse. The proposed measures take conformed dimensions into account, which is a notable feature of the data warehouse. However, the proposed metrics had not been validated. Therefore, the main aim of this study is to corroborate the proposed coupling metrics theoretically against Briand's property-based framework, as well as empirically, using advanced statistical and machine learning techniques. The results indicate that the metrics are well-founded coupling measures and hence significantly contribute towards the structural complexity of the models which further impacts their understandability.
机译：数据仓库的概念模型可用于确定设计初期的质量。过去已经提出了度量以量化这些模型的结构复杂性。这些指标大部分都集中在大小和复杂性的内部质量属性上。不幸的是，没有提出太多措施来评估数据仓库多维模型中的耦合程度。耦合对这些模型的复杂性和质量产生重大影响。在我们以前的工作中，我们提出了一些措施来确定数据仓库的面向对象概念模型中存在的类之间的继承和聚集耦合的范围。提议的措施考虑到了一致的尺寸，这是数据仓库的显着特征。但是，建议的度量标准尚未得到验证。因此，本研究的主要目的是使用先进的统计和机器学习技术，从理论上根据Briand的基于属性的框架，以及从经验上证实所提出的耦合度量。结果表明，度量是有充分根据的耦合度量，因此对模型的结构复杂性有很大贡献，这进一步影响了模型的可理解性。

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