102 citations · 301 across the 47 of their papers we have counts for
6 papers · 1 filter
HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks
Xuye Liu, Dakuo Wang, April Wang +2
Jupyter notebook allows data scientists to write machine learning code together with its documentation in cells. In this paper, we propose a new task of code documentation generati…
A Neural Question Answering System for Basic Questions about Subroutines
Aakash Bansal, Zachary Eberhart, Lingfei Wu +1
A question answering (QA) system is a type of conversational AI that generates natural language answers to questions posed by human users. QA systems often form the backbone of int…
Action Word Prediction for Neural Source Code Summarization
Sakib Haque, Aakash Bansal, Lingfei Wu +1
Source code summarization is the task of creating short, natural language descriptions of source code. Code summarization is the backbone of much software documentation such as Jav…
A Multi-Perspective Architecture for Semantic Code Search
Rajarshi Haldar, Lingfei Wu, Jinjun Xiong +1
The ability to match pieces of code to their corresponding natural language descriptions and vice versa is fundamental for natural language search interfaces to software repositori…
Improved Automatic Summarization of Subroutines via Attention to File Context
Sakib Haque, Alexander LeClair, Lingfei Wu +1
Software documentation largely consists of short, natural language summaries of the subroutines in the software. These summaries help programmers quickly understand what a subrouti…
Improved Code Summarization via a Graph Neural Network
Alexander LeClair, Sakib Haque, Lingfei Wu +1
Automatic source code summarization is the task of generating natural language descriptions for source code. Automatic code summarization is a rapidly expanding research area, espe…