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Identification of high conditional complexity in source code based on statistical analysis

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成果类型:
期刊论文
作者:
Liu, Wei;Huang, Xindi;Hu, Zhigang;Xian, Weicheng
通讯作者:
Liu, Wei(weiliu_china@126.com)
作者机构:
[Liu, Wei; Huang, Xindi] School of Management and Information Engineering, Hunan University of Chinese Medicine, Changsha Hunan, 410208, China
[Hu, Zhigang; Xian, Weicheng] School of Software, Central South University, Changsha Hunan, 410075, China
通讯机构:
School of Management and Information Engineering, Hunan University of Chinese Medicine, Changsha Hunan, China
语种:
英文
关键词:
Conditional complexity;Cyclomatic complexity;Identification of refactoring opportunities;Software metrics;Statistical analysis
期刊:
Revista Tecnica de la Facultad de Ingenieria Universidad del Zulia
ISSN:
0254-0770
年:
2016
卷:
39
期:
11
页码:
1-9
机构署名:
本校为第一且通讯机构
院系归属:
信息科学与工程学院
摘要:
In order to identify the high conditional complexity in source code, a novel approach based on statistical analysis is proposed. According to the statistical analysis of two software metrics which are Method McCabe's Cyclomatic Complexity (MMCC) and Method Average McCabe's Cyclomatic Complexity Per Code Line (MAMCC) in a large number of projects, the probability density functions and cumulative distribution functions for describing distributions of these two metrics are obtained. Moreover, a model for identifying high conditional complexity is built by choosing reasonable threshold of these me...

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