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Columbus, Ohio, USA
June 6, 2005 to June 10, 2005
ISBN: 0-7695-2328-5
pp: 65-71
Wei-Tek Tsai , Arizona State University
Yinong Chen , Arizona State University
Dawei Zhang , Arizona State University
Hai Huang , Arizona State University
Web Services (WS) need to be trustworthy to be used in critical applications. A technique called WS Group Testing has been proposed which can significantly reduce the cost of testing and ranking a large number of WS. A main feature of WS group testing is that it is able to establish the test oracles for the given test inputs from multiple WS and infer the oracles by plural voting. Efficient voting of complex and large number of data is critical to the success of group testing. Current voting techniques are not designed to deal with such a situation. This paper presents efficient voting algorithms that determine the plural value on multi-dimensional data and large number of data. The algorithm uses a clustering method to classify data into regions to identify the plural value. Experiments are designed and performed to concept-prove the algorithms and their applications with group testing.
Web Services Testing, Group Testing, Voting, Clustering
Wei-Tek Tsai, Yinong Chen, Dawei Zhang, Hai Huang, "Voting Multi-Dimensional Data with Deviations for Web Services under Group Testing", ICDCSW, 2005, 2013 IEEE 33rd International Conference on Distributed Computing Systems Workshops, 2013 IEEE 33rd International Conference on Distributed Computing Systems Workshops 2005, pp. 65-71, doi:10.1109/ICDCSW.2005.141
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