285 citations · 521 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
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.…
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…
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…
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…