期刊名称：International Journal of Software Engineering & Applications (IJSEA)
印刷版ISSN：0976-2221
电子版ISSN：0975-9018
出版年度：2013
卷号：4
期号：5
页码：1
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Bad smells are signs of potential problems in code. Detecting bad smells, however, remains timeconsuming for software engineers despite proposals on bad smell detection and refactoring tools. LargeClass is a kind of bad smells caused by large scale, and the detection is hard to achieve automatically. Inthis paper, a Large Class bad smell detection approach based on class length distribution model andcohesion metrics is proposed. In programs, the lengths of classes are confirmed according to the certaindistributions. The class length distribution model is generalized to detect programs after grouping.Meanwhile, cohesion metrics are analyzed for bad smell detection. The bad smell detection experiments ofopen source programs show that Large Class bad smell can be detected effectively and accurately with thisapproach, and refactoring scheme can be proposed for design quality improvements of programs.
关键词：Distribution rule; Class length distribution model; Cohesion metrics; Bad smell detection; refactoring;scheme
