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Implementation of "Automatic Source Code Summarization with Extended Tree-LSTM"
Python Jupyter Notebook
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notebooks Add check_result notebook Dec 2, 2018
parser Update Jul 2, 2019 Change savedata name & Change nl first charactor to lower Dec 2, 2018 Fasten BiLSTM with CuDNN Nov 19, 2018 Remove unused slice Nov 28, 2018
requirements.txt Fix bug Sep 21, 2018 Not shuffle data Nov 22, 2018 Add explicit data sorting (the move is same) Dec 3, 2018 Fix bug (dropout was always .5) Nov 22, 2018

Attention-based Tree-to-Sequence Code Summarization Model

The TensorFlow Eager Execution implementation of Source Code Summarization with Extended Tree-LSTM (Shido+, 2019)


  • Multi-way Tree-LSTM model (Ours)
  • Child-sum Tree-LSTM model
  • N-ary Tree-LSTM model
  • DeepCom (Hu et al.)
  • CODE-NN (Iyer et al.)


  1. Download raw dataset from []
  2. Parse them with parser.jar


  1. Prepare tree-structured data with
    • Run $ python [dir]
  2. Train and evaluate model with
    • See $ python -h
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