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An object-oriented high-level design-based class cohesion metric

机译:面向对象的基于高级设计的类内聚度量

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Context: Class cohesion is an important object-oriented software quality attribute. Assessing class cohesion during the object-oriented design phase is one important way to obtain more comprehensible and maintainable software. In practice, assessing and controlling cohesion in large systems implies measuring it automatically. One issue with the few existing cohesion metrics targeted at the high-level design phase is that they are not based on realistic assumptions and do not fulfill expected mathematical properties. Objective: This paper proposes a High-Level Design (HLD) class cohesion metric, which is based on realistic assumptions, complies with expected mathematical properties, and can be used to automatically assess design quality at early stages using UML diagrams.rnMethod: The notion of similarity between pairs of methods and pairs of attribute types in a class is introduced and used as a basis to introduce a novel high-level design class cohesion metric. The metric considers method-method, attribute-attribute, and attribute-method direct and transitive interactions. We validate this Similarity-based Class Cohesion (SCC) metric theoretically and empirically. The former includes a careful study of the mathematical properties of the metric whereas the latter investigates, using four open source software systems and 10 cohesion metrics, whether SCC is based on realistic assumptions and whether it better explains the presence of faults, from a statistical standpoint, than other comparable cohesion metrics, considered individually or in combination. Results: Results confirm that SCC is based on clearly justified theoretical principles, relies on realistic assumptions, and is an early indicator of quality (fault occurrences).rnConclusion: It is concluded that SCC is both theoretically valid and supported by empirical evidence. It is a better alternative to measure class cohesion than existing HLD class cohesion metrics.
机译:上下文:类凝聚力是重要的面向对象的软件质量属性。在面向对象的设计阶段评估类的内聚性是获得更易理解和可维护的软件的一种重要方法。实际上,在大型系统中评估和控制凝聚力意味着需要对其进行自动测量。以高级设计阶段为目标的少数现有内聚度量标准的一个问题是,它们不是基于现实的假设,并且不能满足预期的数学特性。目的:本文提出了一个高级设计(HLD)类内聚度量标准,该度量标准基于现实的假设,符合预期的数学特性,可用于使用UML图在早期阶段自动评估设计质量。介绍类中的方法对和属性类型对之间的相似性,并以此为基础,介绍一种新颖的高级设计类内聚度量。度量标准考虑方法方法,属性属性以及属性方法的直接和传递交互。我们从理论和经验上验证了这种基于相似度的类内聚(SCC)度量。前者包括对度量标准的数学特性的仔细研究,而后者则使用四个开源软件系统和10个内聚度量标准来调查SCC是否基于现实的假设以及从统计学的角度是否更好地解释了故障的存在,而不是单独或组合考虑的其他类似的内聚度指标。结果:结果证实,SCC基于明确合理的理论原理,依赖于现实的假设,并且是质量(故障发生)的早期指标。rn结论:结论是,SCC在理论上是有效的,并得到经验证据的支持。与现有的HLD类内聚度量相比,它是衡量类内聚的更好选择。

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