METHOD FOR GENERATION OF CODE ANNOTATIONS BASED ON PROGRAM ANALYSIS AND RECURRENT NEURAL NETWORK

摘要

Disclosed is a method for generation of code annotations based on program analysis and a recurrent neural network, comprising the following steps: building a large-scale code library; extracting information included in each Java method within a Java project and dependency information thereof; according to the extracted information and in combination with a heuristic method, filtering and reconstructing the execution code portion of each Java method; obtaining annotations matching the execution code; assembling the filtered code and the corresponding annotations into a code/annotation pair set, and using same as a training set for a code annotation generation model; by means of the obtained training set, using an encoding-decoding model to perform code annotation generation model training; after the model training is complete, performing prediction. The method generates simple and clear annotations, can help developers to understand code functions, accelerates software maintenance processes, and increases software product quality.