PLangRec

Deep-learning Model to Predict the Programming Language from a Single Line of Code

Here you can download the following elements used in the article PLangRec: Deep-learning Model to Predict the Programming Language from a Single Line of Code:

  • Source code used to gather the source code from GitHub, perform language verification, and extract preprocessed lines (i.e., Figure 1 of the article).
  • Keras models of the MLP and BRNN models with best performance (8 layers).
  • Raw evaluation data obtained in the different evaluations presented in the article.
  • Source code and binaries of PLangRec: the web API, web application and Python desktop program, together with the source code used to build and train the MLP and BRNN models.
  • All the samples misclassified by PLangRec in the test dataset, indicating the actual language and the predicted one.
  • The corpus with 8.5 million source code files (21 languages) used to create the dataset (113 GBs).
  • The balanced dataset with 434.18 million samples in 21 different languages.

LICENSE

Copyright 2024 (C) Computational Reflection research group, University of Oviedo. All Rights Reserved.

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