2 citations · 2 across the 5 of their papers we have counts for
8 papers
Evaluating and Improving Static Application Security Testing Tools for Rust
Huaien Zhang, Zhengjie Zhao, Yu Pei +4
Rust has become a popular systems programming language in recent years because of its strong guarantees on memory and concurrency safety. Many types of system software have been re…
Combining LLM and Dynamic Analysis for Universal Testing of Static Application Security Testing Tools
Huaien Zhang, Yu Pei, Hao Chen +1
Static application security testing (SAST) tools help detect potential software vulnerabilities, but they themselves contain faults undermining reliability and usability. Automated…
FuzzAgent: Multi-Agent System for Evolutionary Library Fuzzing
Yunlong Lyu, Peng Chen, Fengyi Wu +3
Library fuzzing is essential for hardening the software supply chain, but adopting it at scale remains expensive. Practitioners still spend substantial effort on environment setup,…
"Tab, Tab, Bug": Security Pitfalls of Next Edit Suggestions in AI-Integrated IDEs
Yunlong Lyu, Yixuan Tang, Peng Chen +4
Modern AI-integrated IDEs are shifting from passive code completion to proactive Next Edit Suggestions (NES). Unlike traditional autocompletion, NES is designed to construct a rich…
Security of AI Agents
Yifeng He, Ethan Wang, Yuyang Rong +2
AI agents have been boosted by large language models. AI agents can function as intelligent assistants and complete tasks on behalf of their users with access to tools and the abil…
FuzzAug: Data Augmentation by Coverage-guided Fuzzing for Neural Test Generation
Yifeng He, Jicheng Wang, Yuyang Rong +1
Testing is essential to modern software engineering for building reliable software. Given the high costs of manually creating test cases, automated test case generation, particular…
LLAMAFUZZ: Large Language Model Enhanced Greybox Fuzzing
Hongxiang Zhang, Yuyang Rong, Yifeng He +1
Greybox fuzzing has achieved success in revealing bugs and vulnerabilities in programs. However, randomized mutation strategies have limited the fuzzer's performance on structured…
IRFuzzer: Specialized Fuzzing for LLVM Backend Code Generation
Yuyang Rong, Zhanghan Yu, Zhenkai Weng +2
Modern compilers, such as LLVM, are complex pieces of software. Due to their complexity, manual testing is unlikely to suffice, yet formal verification is difficult to scale. End-t…