In the last three decades, memory safety issues in system programming languages such as
C or C++ have been one of the most significant sources of security vulnerabilities. However …

Finding software vulnerabilities in concurrent programs is a challenging task due to the size
of the state-space exploration, as the number of interleavings grows exponentially with the …

While CUDA has been the most popular parallel computing platform and programming
model for general purpose GPU computing, CUDA synchronization undergoes significant …

Artificial Neural networks (ANNs) are powerful computing systems employed for various
applications due to their versatility to generalize and to respond to unexpected …

Artificial Neural Networks (ANNs) are being deployed for an increasing number of safety-
critical applications, including autonomous cars and medical diagnosis. However, concerns …

Over the years, researchers have developed many formal method tools to support software
development. However, hardly any studies are conducted to determine whether the actual …

This paper presents a tool for repairing errors in GPU kernels written in CUDA or OpenCL
due to data races and barrier divergence. Our novel extension to prior work can also remove …

Recently, the k-induction algorithm has proven to be a successful approach for both finding
bugs and proving correctness. However, since the algorithm is an incremental approach, it …

This paper presents a technique for repairing errors in GPU kernels written in CUDA or
OpenCL due to data races and barrier divergence. Our novel extension to prior work can …

Operator precedence and associativity are fundamental concepts in the C programming
language that govern the order of evaluation of expressions. Understanding these principles …