30 citations · 31 across the 4 of their papers we have counts for
4 papers
SF: Principled Hybrid Testing With Fuzzing, Symbolic Execution, and Sampling
Lianjing Wang, Yufeng Zhang, Kenli Li +5
Hybrid testing that integrates fuzzing, symbolic execution, and sampling has demonstrated superior testing efficiency compared to individual techniques. However, the state-of-the-a…
DeepGo: Predictive Directed Greybox Fuzzing
Peihong Lin, Pengfei Wang, Xu Zhou +3
The state-of-the-art DGF techniques redefine and optimize the fitness metric to reach the target sites precisely and quickly. However, optimizations for fitness metrics are mainly…
INSTILLER: Towards Efficient and Realistic RTL Fuzzing
Gen Zhang, Pengfei Wang, Tai Yue +3
Bugs exist in hardware, such as CPU. Unlike software bugs, these hardware bugs need to be detected before deployment. Previous fuzzing work in CPU bug detection has several disadva…
MobFuzz: Adaptive Multi-objective Optimization in Gray-box Fuzzing
Gen Zhang, Pengfei Wang, Tai Yue +4
Coverage-guided gray-box fuzzing (CGF) is an efficient software testing technique. There are usually multiple objectives to optimize in CGF. However, existing CGF methods cannot su…