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Publication Detail
Inferring automatic test oracles
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Publication Type:Conference
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Authors:Langdon WB, Yoo S, Harman M
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Publication date:07/07/2017
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Pagination:5, 6
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Published proceedings:Proceedings - 2017 IEEE/ACM 10th International Workshop on Search-Based Software Testing, SBST 2017
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ISBN-13:9781538627891
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Status:Published
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Full Text URL:
Abstract
© 2017 IEEE. We propose the use of search based learning from existing open source test suitesto automatically generate partially correct test oracles. We argue that mutation testing and n-version computing(augmented by deep learningand other soft computingtechniques), will be able to predict whether a program's output is correct sufficiently accurately to be useful.
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