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http://dx.doi.org/10.5391/JKIIS.2002.12.4.328

A Heuristic Metric for Measuring Complexity of Class Inheritance Structures  

Chung, Hong (School of Engineering, Keimyung University)
Kim, Tae-Sik (School of Engineering, Keimyung University)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.12, no.4, 2002 , pp. 328-333 More about this Journal
Abstract
The deeper the hierarchy of a inheritance structure is, the better the reusability of the structure is, but the more difficult the understandability and the maintainability of it is. On the contrary, the shallower the hierarchy is, the worse the abstraction of the inheritance structure is, but the better the understandability and modifiability of it is. Therefore, it is to be desired that a deep hierarchy of a inheritance structure should be split to be shallow for the maintainability of a system. This paper proposed a complexity metric that is based on DIT and NOC of Chidamber and Kemerer, and solved the ambiguity of the metrics of them, which was pointed out by Li. The metric is a simple and heuristic one for measuring the complexity of class inheritance structures by considering the number of ancestor classes and descendant classes and the depth of inheritance hierarchy. This provides a quantitative information for assessing the complexity of a inheritance structure in splitting it.
Keywords
Software Metrics; Inheritance Hierarchy; Software Complexity;
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