MVG-DMA: A multi-view graph with dynamic multi-head attention-based transformer encoder for software requirements classification

Software requirements classification is most important for software quality assurance. Existing graph-based methods fail to capture the syntactic, semantic, and contextual depth of requirement sentences. While recent approaches leverage Graph Neural Networks (GNNs), they suffer from three limitation...

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Автори:	Saratha P, Saswati Mukherjee, Rene Robin C R
Формат:	Artigo
Мова:	Inglês
Опубліковано:	Elsevier 2026-04-01
Серія:	Alexandria Engineering Journal
Предмети:	System Engineering Graph Neural Networks Software Requirements Classification Transformer Encoder Multi-View Learning Natural Language Processing
Онлайн доступ:	http://www.sciencedirect.com/science/article/pii/S1110016826002103
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