Time-efficient code completion model for the R programming language
A Popov, D Orekhov, D Litvinov, N Korolev… - Proceedings of the …, 2021 - aclanthology.org
In this paper we present a deep learning code completion model for the R language. We
introduce several techniques to utilize language modeling based architecture in the code
completion task. With these techniques, the model requires low resources, but still achieves
high quality. We also present an evaluation dataset for the R language completion task. Our
dataset contains multiple autocompletion usage contexts that provides robust validation
results. The dataset is publicly available.
introduce several techniques to utilize language modeling based architecture in the code
completion task. With these techniques, the model requires low resources, but still achieves
high quality. We also present an evaluation dataset for the R language completion task. Our
dataset contains multiple autocompletion usage contexts that provides robust validation
results. The dataset is publicly available.
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