Using machine learning techniques to detect metamorphic relations for programs without test oracles

Much software lacks test oracles, which limits automated testing. Metamorphic testing is one proposed method for automating the testing process for programs without test oracles. Unfortunately, finding the appropriate metamorphic relations required for use in metamorphic testing remains a labor intensive task, which is generally performed by a domain expert or a programmer. In this work we present a novel approach for automatically predicting metamorphic relations using machine learning techniques. Our approach uses a set of features developed using the control flow graph of a function for predicting likely metamorphic relations. We show the effectiveness of our method using a set of real world functions often used in scientific applications.