activity
20192023
most citedCURE: Code-Aware Neural Machine Translation for Automatic Program Repair

285 citations · 521 across the 9 of their papers we have counts for

collaborators

9 papers

cs.SE2023★ 9 cited

How Effective are Large Language Models in Generating Software Specifications?

Danning Xie, Byungwoo Yoo, Nan Jiang +4

Software specifications are essential for many Software Engineering (SE) tasks such as bug detection and test generation. Many existing approaches are proposed to extract the speci…

cs.SE2023★ 4 cited

Symbol Preference Aware Generative Models for Recovering Variable Names from Stripped Binary

Xiangzhe Xu, Zhuo Zhang, Zian Su +8

Decompilation aims to recover the source code form of a binary executable. It has many security applications, such as malware analysis, vulnerability detection, and code hardening.…

cs.SE2023★ 97 cited

How Effective Are Neural Networks for Fixing Security Vulnerabilities

Yi Wu, Nan Jiang, Hung Viet Pham +5

Security vulnerability repair is a difficult task that is in dire need of automation. Two groups of techniques have shown promise: (1) large code language models (LLMs) that have b…

cs.SE2023★ 14 cited

Impact of Code Language Models on Automated Program Repair

Nan Jiang, Kevin Liu, Thibaud Lutellier +1

Automated program repair (APR) aims to help developers improve software reliability by generating patches for buggy programs. Although many code language models (CLM) are developed…

cs.SE2023★ 2 cited

KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair

Nan Jiang, Thibaud Lutellier, Yiling Lou +3

Automated Program Repair (APR) improves software reliability by generating patches for a buggy program automatically. Recent APR techniques leverage deep learning (DL) to build mod…

cs.SE2021★ 79 cited

DocTer: Documentation Guided Fuzzing for Testing Deep Learning API Functions

Danning Xie, Yitong Li, Mijung Kim +4

Input constraints are useful for many software development tasks. For example, input constraints of a function enable the generation of valid inputs, i.e., inputs that follow these…

cs.SE2021★ 285 cited

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

Nan Jiang, Thibaud Lutellier, Lin Tan

Automatic program repair (APR) is crucial to improve software reliability. Recently, neural machine translation (NMT) techniques have been used to fix software bugs automatically.…

cs.LG2020★ 21 cited

Towards Feature Space Adversarial Attack

Qiuling Xu, Guanhong Tao, Siyuan Cheng +1

We propose a new adversarial attack to Deep Neural Networks for image classification. Different from most existing attacks that directly perturb input pixels, our attack focuses on…

cs.SE2019★ 10 cited

ENCORE: Ensemble Learning using Convolution Neural Machine Translation for Automatic Program Repair

Thibaud Lutellier, Lawrence Pang, Viet Hung Pham +2

Automated generate-and-validate (G&V) program repair techniques typically rely on hard-coded rules, only fix bugs following specific patterns, and are hard to adapt to different pr…