DialTest‐EA: An Enhanced Fuzzing Approach With Energy Adjustment for Dialogue Systems via Metamorphic Testing

ABSTRACT Deep neural networks (DNNs) possess potent feature learning capability, enabling them to comprehend natural language, which strongly support developing dialogue systems. However, dialogue systems usually perform incorrect behaviours in some corner cases, which may cause misunderstanding or...

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Veröffentlicht in:	Software testing, verification & reliability verification & reliability, 2025-01, Vol.35 (1), p.n/a
Hauptverfasser:	Chen, Haibo, Chen, Jinfu, Wu, Yucheng, Cai, Saihua, Ahmad, Bilal, Huang, Rubing, Wang, Shengran, Zhang, Chi
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Ant colony optimization Artificial neural networks deep neural network testing dialogue system Economic impact fuzzing Interactive computer systems Machine learning metamorphic testing Mutation Seeds
Online-Zugang:	Volltext
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