Inferring Automatic Test Oracles

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.