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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Research on the Method of Splitting Large Class Diagram Based on Multilevel Partitioning
verfasst von : JinShuai Li, XiaoFei Zhao, BaoShan Sun
Erschienen in: Intelligent Data Engineering and Automated Learning – IDEAL 2017
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Abstract
The UML class diagrams generated in reverse engineering are often large and the readability is poor. In this paper, an automatic split algorithm based on multilevel partitioning technology is proposed. According to the coupling degree between classes, the classes with high coupling are divided into the same part and the class with low coupling are separated. Experimental results show that, compared with the traditional manual division, the class diagram obtained by the automatic splitting method is more readable and consumes less time. Using the automatic splitting method to split the large class diagram can save a lot of time, improving work efficiency greatly.