incorporating qualitative and quantitative factors for software defect prediction

CORC > 软件研究所 > 软件所图书馆 > 会议论文

	incorporating qualitative and quantitative factors for software defect prediction
	Wang Dandan ; Wang Qing ; Hong Zhenghua ; Chen Xichang ; Zhang Liwen ; Yang Ye
	2012
会议名称	2nd International Workshop on Evidential Assessment of Software Technologies, EAST 2012
会议日期	September 22, 2012 - September 22, 2012
会议地点	Lund, Sweden
关键词	Forecasting Outsourcing Principal component analysis
页码	61-65
中文摘要	Defect is an important quality attribute of software. Defect is injected in development process and depended on the maturity level of the processes. How many defects were detected is enough? In any software organization, effort estimation and defect prediction are big challenges. Predicting the number of defects in the early stage of software development life cycle will be more helpful for the organizations to estimate the quality of developed product and optimize the resources schedule. Especially in outsourcing organization, the early precise defect prediction can help them to monitor the supplier's process and establish the criteria to verify the outsourcing products. Chinese development bank (CDB) is such an outsourcing organization, who applied SAM process area of CMMI to manage their outsourcing projects. In this paper, we proposed a prediction mode, which incorporated the qualitative factors from COQUALMO and the quantitative data collected from 21 historic financial projects of CDB. Principal Component Analysis (PCA) method was adopted to analyze the inter-correlated factors, and the key factors were determined to simplify the proposed model. We also evaluated its performance and compared with the software defect introduction (DI) model of COQUALMO. The results show that 66.67% predicted results are better than DI model and 80.5% predicted results have AE which are less than 50 while 95.24% predicted results have AE which are less than 100. Copyright 2012 ACM.
英文摘要	Defect is an important quality attribute of software. Defect is injected in development process and depended on the maturity level of the processes. How many defects were detected is enough? In any software organization, effort estimation and defect prediction are big challenges. Predicting the number of defects in the early stage of software development life cycle will be more helpful for the organizations to estimate the quality of developed product and optimize the resources schedule. Especially in outsourcing organization, the early precise defect prediction can help them to monitor the supplier's process and establish the criteria to verify the outsourcing products. Chinese development bank (CDB) is such an outsourcing organization, who applied SAM process area of CMMI to manage their outsourcing projects. In this paper, we proposed a prediction mode, which incorporated the qualitative factors from COQUALMO and the quantitative data collected from 21 historic financial projects of CDB. Principal Component Analysis (PCA) method was adopted to analyze the inter-correlated factors, and the key factors were determined to simplify the proposed model. We also evaluated its performance and compared with the software defect introduction (DI) model of COQUALMO. The results show that 66.67% predicted results are better than DI model and 80.5% predicted results have AE which are less than 50 while 95.24% predicted results have AE which are less than 100. Copyright 2012 ACM.
收录类别	EI
会议主办者	ACM Special Interest Group on Software Engineering (SIGSOFT); IEEE Computer Society (CS)
会议录	EAST'12 - Proceedings of the 2nd International Workshop on Evidential Assessment of Software Technologies
语种	英语
ISBN号	9781450315098
内容类型	会议论文
源URL	[http://ir.iscas.ac.cn/handle/311060/15874]
专题	软件研究所_软件所图书馆_会议论文
推荐引用方式 GB/T 7714	Wang Dandan,Wang Qing,Hong Zhenghua,et al. incorporating qualitative and quantitative factors for software defect prediction[C]. 见:2nd International Workshop on Evidential Assessment of Software Technologies, EAST 2012. Lund, Sweden. September 22, 2012 - September 22, 2012.