21 citations · 27 across the 9 of their papers we have counts for
3 papers · 1 filter
LLMs are All You Need? Improving Fuzz Testing for MOJO with Large Language Models
Linghan Huang, Peizhou Zhao, Huaming Chen
The rapid development of large language models (LLMs) has revolutionized software testing, particularly fuzz testing, by automating the generation of diverse and effective test inp…
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…
On the Challenges of Fuzzing Techniques via Large Language Models
Linghan Huang, Peizhou Zhao, Huaming Chen +1
In the modern era where software plays a pivotal role, software security and vulnerability analysis are essential for secure software development. Fuzzing test, as an efficient and…