As software vulnerabilities grow in volume and complexity, researchers proposed various
Artificial Intelligence (AI)-based approaches to help under-resourced security analysts to …

After more than twenty-five years of research, memory safety violations remain one of the
major causes of security vulnerabilities in real-world software. Memory-safe languages, like …

Fuzz testing is an active area of research with proposed improvements published at a rapid
pace. Such proposals are assessed empirically: Can they be shown to perform better than …

Code similarity is one promising approach to detect vulnerabilities hidden in software
programs. However, due to the complexity and diversity of source code, current methods …

Common software vulnerabilities can result in severe security breaches, financial losses,
and reputation deterioration and require research effort to improve software security. The …

Data dependence analysis underlies various applications in software quality assurance, yet
existing frameworks/tools for this analysis commonly suffer scalability challenges. We …

Binary lifters convert executables into an intermediate representation (IR) of a compiler
framework. The recovered IR code is generally deemed “analysis friendly,” bridging low …

Many critical codebases are written in C, and most of them use preprocessor directives to
encode variability, effectively encoding software product lines. These preprocessor …

Software projects are complex technical and organizational systems involving large
numbers of artifacts and developers. To understand and tame software complexity, a wide …

Static analysis is a mature field with applications to bug detection, security analysis, program
understanding, optimization, and more. To facilitate these applications, static analysis …