collaborators

5 papers

cs.SE2024

Fuzz4All: Universal Fuzzing with Large Language Models

Chunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian +2

Fuzzing has achieved tremendous success in discovering bugs and vulnerabilities in various software systems. Systems under test (SUTs) that take in programming or formal language a…

cs.SE2024

Keep the Conversation Going: Fixing 162 out of 337 bugs for $0.42 each using ChatGPT

Chunqiu Steven Xia, Lingming Zhang

Automated Program Repair (APR) aims to automatically generate patches for buggy programs. Recent APR work has been focused on leveraging modern Large Language Models (LLMs) to dire…

cs.SE2024

Revisiting the Plastic Surgery Hypothesis via Large Language Models

Chunqiu Steven Xia, Yifeng Ding, Lingming Zhang

Automated Program Repair (APR) aspires to automatically generate patches for an input buggy program. Traditional APR tools typically focus on specific bug types and fixes through t…

cs.SE2024

Practical Program Repair in the Era of Large Pre-trained Language Models

Chunqiu Steven Xia, Yuxiang Wei, Lingming Zhang

Automated Program Repair (APR) aims to help developers automatically patch software bugs. However, current state-of-the-art traditional and learning-based APR techniques face the p…

cs.SE2024

Less Training, More Repairing Please: Revisiting Automated Program Repair via Zero-shot Learning

Chunqiu Steven Xia, Lingming Zhang

Due to the promising future of Automated Program Repair (APR), researchers have proposed various APR techniques, including heuristic-based, template-based, and constraint-based tec…