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Publication Detail
Inferring automatic test oracles
  • Publication Type:
  • Authors:
    Langdon WB, Yoo S, Harman M
  • Publication date:
  • Pagination:
    5, 6
  • Published proceedings:
    Proceedings - 2017 IEEE/ACM 10th International Workshop on Search-Based Software Testing, SBST 2017
  • ISBN-13:
  • Status:
© 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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