21 citations · 46 across the 12 of their papers we have counts for
6 papers · 1 filter
The Data Problem in Software Vulnerability Analysis: Artifacts, Quality, and Consumption
Yu Nong, Yao Du, Tianxiang Xu +1
Learning- and LLM-based software vulnerability analysis is only as trustworthy as the data it is trained and evaluated on, yet that data is rarely examined as a first-class object.…
A Comprehensive Study of Native Code Bugs in Python Applications
Haoran Yang, Haipeng Cai
The impact of Python applications has been evidenced by their widespread presence in some of the most impactful software domains, such as machine learning frameworks and scientific…
Dissecting Software Graphs: Structural Insights for Driver-Guided Fuzzing
Baihong Chen, Hua Ming, Weifeng Pan +3
Many software systems expose multiple execution modes through command-line options, subcommands, and configuration flags. For such programs, fuzzing depends on both mutated inputs…
Neuro-Symbolic Proof-of-Vulnerability Generation with Open-Weight Models
Yu Nong, Haipeng Cai
Software vulnerabilities are persistent, but validating them remains difficult: a Proof-of-Vulnerability (PoV) requires a concrete input that triggers the vulnerable behavior, yet…
VulScribeR: Exploring RAG-based Vulnerability Augmentation with LLMs
Seyed Shayan Daneshvar, Yu Nong, Xu Yang +2
Detecting vulnerabilities is vital for software security, yet deep learning-based vulnerability detectors (DLVD) face a data shortage, which limits their effectiveness. Data augmen…
From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future
Haolin Jin, Linghan Huang, Haipeng Cai +3
With the rise of large language models (LLMs), researchers are increasingly exploring their applications in var ious vertical domains, such as software engineering. LLMs have achie…