A data race in a kernel is an important class of bugs, critically impacting the reliability and
security of the associated system. As a result of a race, the kernel may become …

Debugging software failures in deployed systems is important because they impact real
users and customers. However, debugging such failures is notoriously hard in practice …

Concurrency bugs are hard to find, reproduce, and debug. They often escape rigorous in-
house testing, but result in large-scale outages in production. Existing concurrency-bug …

Modern data center applications exhibit deep software stacks, resulting in large instruction
footprints that frequently cause instruction cache misses degrading performance, cost, and …

While current bug detection techniques for concurrent software focus on unearthing low-
level issues such as data races or deadlocks, they often fall short of discovering more …

Random-based approaches and heuristics are commonly used in kernel concurrency
testing due to the massive scale of modern kernels and corresponding interleaving space …

A kernel data race is notoriously challenging to detect, reproduce, and diagnose, mainly
caused by nondeterministic thread interleaving. The kernel data race has a critical security …

The increasing cost of successful cyberattacks has caused a mindset shift, whereby
defenders now employ proactive defenses, namely software bug hunting, alongside existing …

Modern processors employ a decoupled frontend with Fetch Directed Instruction Prefetching
(FDIP) to avoid frontend stalls in data center applications. However, the large branch …

Modern data center applications experience frequent branch mispredictions–degrading
performance, increasing cost, and reducing energy efficiency in data centers. Even the state …