  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 Type-associated 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.
