A Hybrid Approach for Inference between Behavioral Exception API Documentation and Implementations, and Its Applications
Abstract
Automatically producing behavioral exception (BE) API documentation helps developers correctly use the libraries. The state-of-the-art approaches are either rule-based, which is too restrictive in its applicability, or deep learning (DL)-based, which requires large training dataset. To address that, we propose StatGen, a novel hybrid approach between statistical machine translation (SMT) and tree-structured translation to generate the BE documentation for any code and vice versa. We consider the documentation and source code of an API method as the two abstraction levels of the same intent. StatGen is specifically designed for this two-way inference, and takes advantage of their structures for higher accuracy.
BibTeX
@inproceedings{Nguyen-al:ASE22,
author = {Hoan Anh Nguyen and
Hung Dang Phan and
Syeda Khairunnesa Samantha and
Son Nguyen and
Aashish Yadavally and
Shaohua Wang and
Hridesh Rajan and
Tien N. Nguyen},
title = {A Hybrid Approach for Inference between Behavioral Exception {API} Documentation and Implementations, and Its Applications},
booktitle = {ASE},
pages = {2:1--2:13},
publisher = {{ACM}},
year = {2022},
}