Java vulnerability classification method based on natural language processing and deep forest

The invention discloses a Java vulnerability classification method based on natural language processing and a deep forest, and belongs to the technical field of source code vulnerability mining and classification. The method mainly comprises two aspects of vulnerability source code feature extraction and representation and a vulnerability source code classification method. Aiming at the problems of low efficiency and high false alarm rate of a current Java source code static analysis method, a source code is analyzed into an abstract syntax tree, the abstract syntax tree is cut into expression sub-trees through an NLP-based ASTNN coding layer, the expression sub-trees are traversed twice to obtain a statement sequence, and final vector representation of the source code is obtained through multi-granularity scanning. The vector representations are then classified through a cascade forest. An OWASP vulnerability data set is selected as a sample in an experiment, and the effectiveness of the Java source code vul