Code Generation as a Dual Task of Code Summarization

code-gen/cgcs • • NeurIPS 2019

Code summarization (CS) and code generation (CG) are two crucial tasks in the field of automatic software development.

Automatic Source Code Summarization with Extended Tree-LSTM

sh1doy/summarization_tf • • 19 Jun 2019

Neural machine translation models are used to automatically generate a document from given source code since this can be regarded as a machine translation task.

Recommendations for Datasets for Source Code Summarization

transms/m2ts • • NAACL 2019

The main use for these descriptions is in software documentation e. g. the one-sentence Java method descriptions in JavaDocs.

Improving Automatic Source Code Summarization via Deep Reinforcement Learning

mf1832146/tree_transformer_2.0 • • 17 Nov 2018

To the best of our knowledge, most state-of-the-art approaches follow an encoder-decoder framework which encodes the code into a hidden space and then decode it into natural language space, suffering from two major drawbacks: a) Their encoders only consider the sequential content of code, ignoring the tree structure which is also critical for the task of code summarization, b) Their decoders are typically trained to predict the next word by maximizing the likelihood of next ground-truth word with previous ground-truth word given.

Structured Neural Summarization

microsoft/ptgnn • • ICLR 2019

Summarization of long sequences into a concise statement is a core problem in natural language processing, requiring non-trivial understanding of the input.

code2seq: Generating Sequences from Structured Representations of Code

tech-srl/code2seq • • ICLR 2019

The ability to generate natural language sequences from source code snippets has a variety of applications such as code summarization, documentation, and retrieval.

Summarizing Source Code using a Neural Attention Model

sriniiyer/codenn • • ACL 2016