CppCon 2026

Notifiers are a critical synchronization primitive in task-parallel programming systems such as Intel TBB and Taskflow, responsible for efficiently sleeping and waking worker threads as tasks become unavailable and available over and over again, directly impacting scheduler throughput and latency. Correctness here is non-negotiable: a single missed wakeup can significantly hamper the performance of an entire program. Yet writing strong unit tests for notifiers is notoriously difficult, because the bugs they target, lost wakeups, spurious wakes, race conditions, are timing-dependent, non-deterministic, and often only surface under specific thread interleavings that are hard to force reliably.

The problem is compounded in practice. Notifier implementations evolve constantly: small algorithmic tweaks, memory ordering changes, and refactors across systems demand a fresh round of carefully constructed tests. This is tedious, expertise-heavy work that takes a lot of time and engineering effort. In this talk, we explore using Large Language Models (LLMs) to automate the generation of the unit tests for notifiers. Specifically, we will demonstrate how LLM-generated tests, guided by proper prompts can systematically stress the two-phase wait protocol across Notifiers in Taskflow. We will show this in a widely used Notifier implemented in Taskflow. We are able to find an undiscovered bug that has been existing in the project.