Deep API Learning

It is a PyTorch implementation of deepAPI. See Deep API Learning for more details.

Prerequisites

• PyTorch 0.4
• Python 3.6
• Numpy

Usage

Dataset

download data from Google Driver and save them to the ./data folder

Train

$ python train.py will run default training and save model to ./output

Test

Then you can run the model by:

python sample.py

The outputs will be printed to stdout and generated responses will be saved at results.txt in the ./output/ path.

References

If you use any source codes or datasets included in this toolkit in your work, please cite the following paper:

@inproceedings{gu2016deepapi,
    author = {Gu, Xiaodong and Zhang, Hongyu and Zhang, Dongmei and Kim, Sunghun},
    title = {Deep API Learning},
    booktitle = {Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering},
    series = {FSE 2016},
    year = {2016},
    location = {Seattle, WA, USA},
    pages = {631--642},
    publisher = {ACM},
    address = {New York, NY, USA},
}