Concurrency patterns address the challenges of executing multiple computations simultaneously, managing shared resources, synchronizing threads, and structuring asynchronous workflows. These patterns are essential for building responsive, high-throughput systems.

Patterns in This Category

Pattern	Purpose	Key Mechanism
Producer-Consumer	Decouple data production from consumption	Shared bounded queue
Read-Write Lock	Allow concurrent reads, exclusive writes	RWMutex / RWLock
Thread Pool	Reuse a fixed set of workers	Worker pool with task queue
Future / Promise	Represent a value not yet available	Async result placeholder
Actor Model	Isolate state behind message-passing actors	Mailbox queues
Reactor	Demultiplex I/O events on a single thread	Event loop + handlers
Monitor	Protect shared state with mutex + conditions	Condition variables
Active Object	Decouple method invocation from execution	Request queue + scheduler

When to Use Concurrency Patterns

I/O-bound workloads: Reactor, Future/Promise, Actor Model
CPU-bound workloads: Thread Pool, Producer-Consumer
Shared mutable state: Monitor, Read-Write Lock
Message-driven architectures: Actor Model, Active Object
Event-driven systems: Reactor

General Principles

Prefer message passing over shared memory when possible.
Minimize critical sections to reduce contention.
Avoid nested locks to prevent deadlocks.
Use bounded queues to apply backpressure.
Design for cancellation and timeout in all async operations.