20 citations · 48 across the 17 of their papers we have counts for
8 papers · 1 filter
APIDA-Chat: Structured Synthesis of API Search Dialogues to Bootstrap Conversational Agents
Zachary Eberhart, Collin McMillan
Large-language-model assistants are suitable for explaining popular APIs, yet they falter on niche or proprietary libraries because the multi-turn dialogue data needed for fine-tun…
NaturalEdit: Code Modification through Direct Interaction with Adaptive Natural Language Representation
Ningzhi Tang, David Meininger, Gelei Xu +4
Code modification requires developers to comprehend code, plan changes, articulate intent, and validate outcomes, making it cognitively demanding. While natural language (NL) code…
Exploring Direct Instruction and Summary-Mediated Prompting in LLM-Assisted Code Modification
Ningzhi Tang, Emory Smith, Yu Huang +2
This paper presents a study of using large language models (LLMs) in modifying existing code. While LLMs for generating code have been widely studied, their role in code modificati…
EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention
Yifan Zhang, Chen Huang, Yueke Zhang +5
Code Language Models (CodeLLMs) learn token importance from data correlations, whereas human developers attend selectively to semantically salient code. We present EyeMulator, a mo…
Human Attention During Localization of Memory Bugs in C Programs
Emory Michaels, Robert Wallace, Matthew Robison +2
This paper presents a study of human visual attention during localization of memory bugs in C. Human visual attention refers to the mechanical processes by which we selectively pro…
AI-Mediated Code Comment Improvement
Maria Dhakal, Chia-Yi Su, Robert Wallace +5
This paper describes an approach to improve code comments along different quality axes by rewriting those comments with customized Artificial Intelligence (AI)-based tools. We cond…
Do Code LLMs Do Static Analysis?
Chia-Yi Su, Collin McMillan
This paper investigates code LLMs' capability of static analysis during code intelligence tasks such as code summarization and generation. Code LLMs are now household names for the…
Which Code Statements Implement Privacy Behaviors in Android Applications?
Chia-Yi Su, Aakash Bansal, Vijayanta Jain +3
A "privacy behavior" in software is an action where the software uses personal information for a service or a feature, such as a website using location to provide content relevant…