TAG : Type Auxiliary Guiding for Code Comment Generation
Ruichu Cai, Zhihao Liang, Boyan Xu, zijian li, Yuexing Hao, Yao Chen · 2020
Existing leading code comment generation approaches with the structure-to-sequence framework ignores the type information of the interpretation of the code, e.g., operator, string, etc.However, introducing the type information into the existing framework is non-trivial due to the hierarchical dependence among the type information.In order to address the issues above, we propose a Type Auxiliary Guiding encoder-decoder framework for the code comment generation task which considers the source code as an N-ary tree with type information associated with each node.Specifically, our framework is featured with a Typeassociated Encoder and a Type-restricted Decoder which enables adaptive summarization of the source code.We further propose a hierarchical reinforcement learning method to resolve the training difficulties of our proposed framework.Extensive evaluations demonstrate the state-of-the-art performance of our framework with both the auto-evaluated metrics and case studies.