5 papers
A Comparative Study of Fuzzers and Static Analysis Tools for Finding Memory Unsafety in C and C++
Keno Hassler, Philipp Görz, Stephan Lipp
Over 70% of security vulnerabilities in critical software systems today result from memory safety violations. To address this challenge, fuzzing and static analysis are widely used…
VeriGrey: Greybox Agent Validation
Yuntong Zhang, Sungmin Kang, Ruijie Meng +2
Agentic AI has been a topic of great interest recently. A Large Language Model (LLM) agent involves one or more LLMs in the back-end. In the front end, it conducts autonomous decis…
Incoherence as Oracle-less Measure of Error in LLM-Based Code Generation
Thomas Valentin, Ardi Madadi, Gaetano Sapia +1
Generating code from a natural language programming task is one of the most successful applications of Large Language Models (LLMs). Yet, the generated program may be buggy. Withou…
Bootstrapping Fuzzers for Compilers of Low-Resource Language Dialects Using Language Models
Sairam Vaidya, Marcel Böhme, Loris D'Antoni
Modern extensible compiler frameworks-such as MLIR-enable rapid creation of domain-specific language dialects. This flexibility, however, makes correctness harder to ensure as the…
On Interaction Effects in Greybox Fuzzing
Konstantinos Kitsios, Marcel Böhme, Alberto Bacchelli
A greybox fuzzer is an automated software testing tool that generates new test inputs by applying randomly chosen mutators (e.g., flipping a bit or deleting a block of bytes) to a…