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Code and Data for the "On Using Machine Learning to Identify Knowledge in API Reference Documentation" paper

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dfucci/api-doc-kn-identification

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api-doc-kn-identification

Terms of use

Please, see our license.
When (re-)using (part) of this work, you must cite the following publication:

@inproceedings{FMM19,
  title={On Using Machine Learning to Identify Knowledge in API Reference Documentation},
  author={Fucci, Davide and Mollaalizadehbahnemiri Alireza and Maalej, Walid},
  booktitle={27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering},
  pages={103--112},
  year={2019},
  doi={10.1145/3338906.3338943}
  organization={IEEE}
}

How to

This project provides NLP tools based on LSTM for Multi-Lable Calssification of Documents.

To run the lstm classifier:

python scripts/multi_label_classifier_lstm.py <glove_path> <embedding_dim> <train_data_path> <test_data_path> <result_path> <train_embeddings>

*train_embeddings: False (for CC), True (for CCOTF)

dependencies:

  • anaconda
  • keras
  • sklearn
  • csv

path to the embeddings of each model:

CC & CCOTF: http://nlp.stanford.edu/data/glove.840B.300d.zip

StackOverflow (SO): Can be requested from the authors.

StackOverflow API (SOAPI): Can be requested from the authors.

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Code and Data for the "On Using Machine Learning to Identify Knowledge in API Reference Documentation" paper

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