The Source Code Comment Generation based on Abstract Syntax Tree
DOI:
https://doi.org/10.54097/fcis.v5i3.13837Keywords:
Deep Learning, Source Code Comment Generation, Abstract Syntax TreeAbstract
Code summarization provides the main aim described in natural language of the given function; it can benefit many tasks in software engineering. Due to the special grammar and syntax structure of programming languages and various shortcomings of different deep neural networks, the accuracy of existing code summarization approaches is not good enough. We proposes to use abstract syntax trees for source code summarization .Our solution is inspired by recent advances in neural machine translation, as well as an approach called SBT by Hu et al. We evaluate our approach using the automated metric BLEU and compare it to other relevant models.
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