6 papers · 1 filter
EyeTrans: Merging Human and Machine Attention for Neural Code Summarization
Yifan Zhang, Jiliang Li, Zachary Karas +5
Neural code summarization leverages deep learning models to automatically generate brief natural language summaries of code snippets. The development of Transformer models has led…
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…
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…