Research in software testing often involves the development of software prototypes. Like any
piece of software, there are challenges in the development, use and verification of such …

In this study, we investigate the limits of the current state of the art AI system for detecting
buffer overflows and compare it with current static analysis tools. To do so, we developed a …

Fuzzing has emerged as the most effective bug-finding technique. The output of a fuzzer is a
set of proof-of-concept (PoC) test cases for all observed" unique''crashes. It costs developers …

The popularity of coverage-guided greybox fuzzers has led to a tsunami of security-critical
bugs that developers must prioritize and fix. Knowing the capabilities a bug exposes (eg …

We describe and evaluate a novel approach to automated test generation that exploits
fuzzing and Bounded Model Checking (BMC) engines to detect security vulnerabilities in C …

Reproducing production failures is crucial for software reliability. Alas, existing bug
reproduction approaches are not suitable for production systems because they are not …

With the rapid development and widespread application of blockchain technology in recent
years, smart contracts running on blockchains often face security vulnerability problems …

Traditional techniques for smart contract vulnerability detection rely on fixed expert criteria to
discover vulnerabilities, which are less generalizable, scalable, and accurate. Deep learning …

Concolic execution is a dynamic twist of symbolic execution designed with scalability in
mind. Recent concolic executors heavily rely on program instrumentation to achieve such …

As a national critical infrastructure, the smart grid has attracted widespread attention for its
cybersecurity issues. The development towards an intelligent, digital, and Internetconnected …