Assemble Foundation Models for Automatic Code Summarization. (arXiv:2201.05222v1 [cs.SE])

Automatic code summarization is beneficial to software development and
maintenance since it reduces the burden of manual tasks. Currently, artificial
intelligence is undergoing a paradigm shift. The foundation models pretrained
on massive data and finetuned to downstream tasks surpass specially customized
models. This trend inspired us to consider reusing foundation models instead of
learning from scratch. Based on this, we propose a flexible and robust approach
for automatic code summarization based on neural networks. We assemble
available foundation models, such …

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