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NaturalCC

swMATH ID: 36364
Software Authors: Yao Wan, Yang He, Jian-Guo Zhang, Yulei Sui, Hai Jin, Guandong Xu, Caiming Xiong, Philip S. Yu
Description: NaturalCC: A Toolkit to Naturalize the Source Code Corpus. We present NaturalCC, an efficient and extensible toolkit to bridge the gap between natural language and programming language, and facilitate the research on big code analysis. Using NaturalCC, researchers both from natural language or programming language communities can quickly and easily reproduce the state-of-the-art baselines and implement their approach. NaturalCC is built upon Fairseq and PyTorch, providing (1) an efficient computation with multi-GPU and mixed-precision data processing for fast model training, (2) a modular and extensible framework that makes it easy to reproduce or implement an approach for big code analysis, and (3) a command line interface and a graphical user interface to demonstrate each model’s performance. Currently, we have included several state-of-the-art baselines across different tasks (e.g., code completion, code comment generation, and code retrieval) for demonstration. The video of this demo is available at this https URL.
Homepage: https://xcodemind.github.io
Source Code:  https://github.com/CGCL-codes/naturalcc
Dependencies: Python
Keywords: Software Engineering; arXiv_cs.SE; natural language; programming language; Natural language processing; NLP; programming language analysis; big code; toolkit
Related Software: CodeBERT; VulDeePecker; RoBERTa; fairseq; AllenNLP; code2seq; BERT; Python
Cited in: 0 Documents

Standard Articles

1 Publication describing the Software Year
NaturalCC: A Toolkit to Naturalize the Source Code Corpus arXiv
Yao Wan, Yang He, Jian-Guo Zhang, Yulei Sui, Hai Jin, Guandong Xu, Caiming Xiong, Philip S. Yu
2020