Software Defect Prediction Based on Gated Hierarchical LSTMs

Software defect prediction, aimed at assisting software practitioners in allocating test resources more efficiently, predicts the potential defective modules in software products. With the development of defect prediction technology, the inability of traditional software features to capture semantic...

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Veröffentlicht in:	IEEE transactions on reliability 2021-06, Vol.70 (2), p.711-727
Hauptverfasser:	Wang, Hao, Zhuang, Weiyuan, Zhang, Xiaofang
Format:	Artikel
Sprache:	eng
Schlagworte:	Abstract syntax tree (AST) Feature extraction hierarchical model Logic gates long short-term memory networks (LSTM) Networks Neurons Prediction models Predictive models Recurrent neural networks Semantics Software software defect prediction Source code
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