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Title:
distribution-aware mutation analysis
Author: Sun Chang-Ai ; Wang Guan ; Cai Kai-Yuan ; Chen Tsong Yueh
Source: Proceedings - International Computer Software and Applications Conference
Conference Name: 36th Annual IEEE International Computer Software and Applications Conference Workshops, COMPSACW 2012
Conference Date: July 16, 2012 - July 20, 2012
Issued Date: 2012
Conference Place: Izmir, Turkey
Keyword: Testing ; Web services
Indexed Type: EI
ISSN: 0730-3157
ISBN: 9780769547589
Department: (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
Sponsorship: IEEE; IEEE Computer Society
Abstract: 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.
English Abstract: 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.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15829
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Sun Chang-Ai,Wang Guan,Cai Kai-Yuan,et al. distribution-aware mutation analysis[C]. 见:36th Annual IEEE International Computer Software and Applications Conference Workshops, COMPSACW 2012. Izmir, Turkey. July 16, 2012 - July 20, 2012.
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