102 citations · 149 across the 23 of their papers we have counts for
9 papers · 1 filter
Revisiting File Context for Source Code Summarization
Aakash Bansal, Chia-Yi Su, Collin McMillan
Source code summarization is the task of writing natural language descriptions of source code. A typical use case is generating short summaries of subroutines for use in API docume…
Modeling Programmer Attention as Scanpath Prediction
Aakash Bansal, Chia-Yi Su, Zachary Karas +4
This paper launches a new effort at modeling programmer attention by predicting eye movement scanpaths. Programmer attention refers to what information people intake when performin…
Distilled GPT for Source Code Summarization
Chia-Yi Su, Collin McMillan
A code summary is a brief natural language description of source code. Summaries are usually only a single sentence long, and yet form the backbone of developer documentation. A sh…
Semantic Similarity Loss for Neural Source Code Summarization
Chia-Yi Su, Collin McMillan
This paper presents a procedure for and evaluation of using a semantic similarity metric as a loss function for neural source code summarization. Code summarization is the task of…
Statement-based Memory for Neural Source Code Summarization
Aakash Bansal, Siyuan Jiang, Sakib Haque +1
Source code summarization is the task of writing natural language descriptions of source code behavior. Code summarization underpins software documentation for programmers. Short d…
Towards Fine-Grained Localization of Privacy Behaviors
Vijayanta Jain, Sepideh Ghanavati, Sai Teja Peddinti +1
Mobile applications are required to give privacy notices to users when they collect or share personal information. Creating consistent and concise privacy notices can be a challeng…
Towards Modeling Human Attention from Eye Movements for Neural Source Code Summarization
Aakash Bansal, Bonita Sharif, Collin McMillan
Neural source code summarization is the task of generating natural language descriptions of source code behavior using neural networks. A fundamental component of most neural model…
A Language Model of Java Methods with Train/Test Deduplication
Chia-Yi Su, Aakash Bansal, Vijayanta Jain +2
This tool demonstration presents a research toolkit for a language model of Java source code. The target audience includes researchers studying problems at the granularity level of…
Label Smoothing Improves Neural Source Code Summarization
Sakib Haque, Aakash Bansal, Collin McMillan
Label smoothing is a regularization technique for neural networks. Normally neural models are trained to an output distribution that is a vector with a single 1 for the correct pre…