DeepAbstraction++: Enhancing Test Prioritization Performance via Combined Parameterized Boxes
Hamzah Al-Qadasi,
Yliès Falcone,
Saddek Bensalem
Abstract:In artificial intelligence testing, there is an increased focus on enhancing the efficiency of test prioritization methods within deep learning systems. Subsequently, the DeepAbstraction algorithm has recently become one of the leading techniques in this area. It employs a box-abstraction concept, the efficiency of which depends on the tau parameter, the clustering parameter, that influences the size of these boxes. The conclusion of the previous experiments using tau values of 0.4 or 0.05 has failed to produc… Show more
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