Concurrency bugs are extremely difficult to detect. Recently, several dynamic techniques
achieve sound analysis. M2 is even complete for two threads. It is designed to decide …

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 …

Concurrent programs are notoriously hard to write correctly, as scheduling nondeterminism
introduces subtle errors that are both hard to detect and to reproduce. The most common …

Writing concurrent programs is highly error-prone due to the nondeterminism in interprocess
communication. The most reliable indicators of errors in concurrency are data races, which …

Trace theory (formulated by Mazurkiewicz in 1987) is a principled framework for defining
equivalence relations for concurrent program runs based on a commutativity relation over …

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 …

Happens before-based dynamic analysis is the go-to technique for detecting data races in
large scale software projects due to the absence of false positive reports. However, such …

Writing concurrent programs is notoriously hard due to scheduling non-determinism. The
most common concurrency bugs are data races, which are accesses to a shared resource …

Multi-threaded programs are challenging to write. Developers often need to reason about a
prohibitively large number of thread interleavings to reason about the behavior of software …

Data races are egregious concurrency bugs that are especially problematic in performance-
oriented GPU codes where large thread counts and multiple shared memory regions tend to …