What is it about?
Its main idea is learning key features from Programs’ syntaxes and semantics via Attention-based recurrent neural network.
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Why is it important?
Programs have their own particular syntactic structures and rich semantic information hidden in ASTs, which help analyzing and locating defects more accurately. Therefore, leveraging deep learning methods to mine hidden features of ASTs can generate significant features that better reflect the code context information, leading to more accurate software defect prediction.
Perspectives
Writing this article was a great pleasure as it has co-authors whom I have had long standing collaborations.
Xuyang Diao
Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, China
Read the Original
This page is a summary of: Software Defect Prediction via Attention-Based Recurrent Neural Network, Scientific Programming, April 2019, Hindawi Publishing Corporation,
DOI: 10.1155/2019/6230953.
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