Abstract

Bad smells are signs of potential problems in code. Detecting bad smells, however, remains time consuming for software engineers despite proposals on bad smell detection and refactoring tools. Large Class is a kind of bad smells caused by large scale, and the detection is hard to achieve automatically. In this paper, a Large Class bad smell detection approach based on class length distribution model and cohesion metrics is proposed. In programs, the lengths of care confirmed according to the certain distributions. 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 of open source programs show that Large Class bad smell can be detected effectively and accurately with this approach, and refactoring scheme can be proposed for design quality improvements of programs.

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