Widely used data race detectors, including the state-of-the-art FastTrack algorithm, incur
performance costs that are acceptable for regular in-house testing, but miss races detectable …

Dynamic program analysis can predict data races knowable from an observed execution,
but existing predictive analyses either miss races or cannot analyze full program executions …

Data races are a real problem for parallel software, yet hard to detect. Sound predictive
analysis observes a program execution and detects data races that exist in some other …

This paper presents Fast Instrumentation Bias (FIB), a sound and complete dynamic data
race detection algorithm that improves performance by reducing or eliminating the costs of …

Data races are one of the main culprits behind the complexity of multithreaded
programming. Existing data race detectors require large amounts of metadata for each …

With the development of the network, there are more and more multi-thread programs. Multi-
thread applications have complex operating states and suffer from data race problem …

The high degree of parallelism and relatively complicated synchronization mechanisms in
GPUs make writing correct kernels difficult. Data races pose one such concurrency …

Existing data race detectors for task-based programs incur significant run time and space
overheads. The overheads arise because of frequent lookups in fine-grained tree data …

Modern shared-memory systems have erroneous, undefined behavior for programs that are
not well synchronized. A promising solution is to provide fail-stop memory consistency …

Data races pose a fundamental issue plaguing the reliability of parallel software. A shared-
memory program has a data race if two conflicting memory accesses (accesses to the same …