关键词: 注意力机制, 图神经网络, 代码理解, 程序分类

Abstract:

In the field of source code mining, the program classification task is the basic work to understand source code. Although the Natural Language Processing（NLP） based models and the abstract syntax tree based models have been proposed to classify computer programs, these works have not considered data flow, control flow and other data information from source code. In order to solve the problem, this paper proposes a method to construct code graph EAST which contains data information and grammatical structure, and realizes program classification through combining Gating Graph Attention Neural Network（GGANN） model with attention mechanism. The attention mechanism of GGANN model takes the different topological structure of nodes into account，so as to improve the information dissemination process. Experiments have shown that the improved GGANN model achieves over 98% accuracy in program classification tasks.

Key words: attention mechanism, graph neural network, code understanding, program classification