distribution-aware mutation analysis

ISCAS OpenIR

	distribution-aware mutation analysis
	Sun Chang-Ai; Wang Guan; Cai Kai-Yuan; Chen Tsong Yueh
	2012
会议名称	36th Annual IEEE International Computer Software and Applications Conference Workshops, COMPSACW 2012
会议录名称	Proceedings - International Computer Software and Applications Conference
页码	170-175
会议日期	July 16, 2012 - July 20, 2012
会议地点	Izmir, Turkey
收录类别	EI
ISSN	0730-3157
ISBN	9780769547589
部门归属	(1) School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China; (2) Department of Automatic Control Beijing University of Aeronautics and Astronautics Beijing China; (3) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Science Beijing China; (4) Facuity of Information and Communication Technologies Swinburne University of Technology Melbourne VIC Australia
摘要	Mutation analysis is widely employed to evaluate the effectiveness of various software testing techniques. In most situations, mutation operators are uniformly applied to the original programs, while the faults tend to be clustered in practice. This may result in the inappropriate simulation of faults, and thus cannot deliver the reliable evaluation results. To overcome this, we propose a distribution-aware mutation analysis technique and conducted empirical studies to investigate the impact of the mutation distribution on the effectiveness evaluation of testing techniques. As an illustration, we select the commonly practiced random testing technique and two versions of dynamic random testing techniques and apply them to testing Web services. Results of empirical studies suggest that the mutation distribution significantly affects the evaluation results. This observation further indicates that the effectiveness of testing techniques previously evaluated with the uniform mutation analysis needs further realignments. © 2012 IEEE.; Mutation analysis is widely employed to evaluate the effectiveness of various software testing techniques. In most situations, mutation operators are uniformly applied to the original programs, while the faults tend to be clustered in practice. This may result in the inappropriate simulation of faults, and thus cannot deliver the reliable evaluation results. To overcome this, we propose a distribution-aware mutation analysis technique and conducted empirical studies to investigate the impact of the mutation distribution on the effectiveness evaluation of testing techniques. As an illustration, we select the commonly practiced random testing technique and two versions of dynamic random testing techniques and apply them to testing Web services. Results of empirical studies suggest that the mutation distribution significantly affects the evaluation results. This observation further indicates that the effectiveness of testing techniques previously evaluated with the uniform mutation analysis needs further realignments. © 2012 IEEE.
关键词	Testing Web Services
主办者	IEEE; IEEE Computer Society
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/15829
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Sun Chang-Ai,Wang Guan,Cai Kai-Yuan,et al. distribution-aware mutation analysis[C],2012:170-175.