Nan Jiang

About

I am a third-year Ph.D. student majoring in Computer Science at Purdue University. Currently, I am working with Prof. Lin Tan about leveraging natural language processing techniques on automatic program repair. Specifically, we are trying to build a deep-learning-based encoder-decoder tool to generate patches for given faulty programs. My research interests mainly focus on applying deep learning techniques to help software testing, software repair, and software analysis.

Education

Purdue University

United States of America
→
Ph.D.

Peking University

China
→
Bachelor of Science

Publications

Show Me Why It’s Correct: Saving 1/3 of Debugging Time in Program Repair with Interactive Runtime Comparison

Proceedings of the ACM on Programming Languages

journal-article

ReSym: Harnessing LLMs to Recover Variable and Data Structure Symbols from Stripped Binaries

conference-paper

A Deep Dive into Large Language Models for Automated Bug Localization and Repair

Proceedings of the ACM on Software Engineering

journal-article

A Deep Dive into Large Language Models for Automated Bug Localization and Repair

Proceedings of the ACM on Software Engineering

conference-paper

RepairCAT: Applying Large Language Model to Fix Bugs in AI-Generated Programs

conference-paper

How Effective Are Neural Networks for Fixing Security Vulnerabilities

Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis

conference-paper

Impact of Code Language Models on Automated Program Repair

2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)

conference-paper

KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair

2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)

conference-paper

Quantifying the spatial homogeneity of urban road networks via graph neural networks

Nature Machine Intelligence

journal-article

CURE: Code-Aware Neural Machine Translation for Automatic Program Repair

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)

conference-paper