Classical synchronization problem: The Producer–Consumer problem can be solved using which synchronization constructs or mechanisms?

Introduction / Context:
The Producer–Consumer problem is a canonical concurrency challenge where producers generate data and consumers process it while sharing a bounded buffer. The aim is to prevent race conditions, buffer overflows, and starvation. Multiple synchronization abstractions solve this problem.

Given Data / Assumptions:

• A bounded buffer exists between producers and consumers.
• Correctness requires mutual exclusion on the buffer and coordination on its empty/full state.
• We are evaluating well-known OS/concurrency mechanisms.

Concept / Approach:

Semaphores (counting and binary) can enforce mutual exclusion (mutex) and signal buffer space or data availability. Event counters (and condition variables) can coordinate wakeups when buffer states change. Monitors encapsulate shared data and operations with implicit mutual exclusion and condition variables for waiting/signaling on buffer-full or buffer-empty conditions.

Step-by-Step Solution:

Verification / Alternative check:

Reference solutions in operating systems textbooks show working implementations using any of the listed abstractions, proving all are valid approaches.

Why Other Options Are Wrong:

• semaphores, event counters, monitors (individually): Each is acceptable but incomplete; the comprehensive answer is that all listed can solve it.
• None of the above: Incorrect, because each offered mechanism is suitable when applied correctly.

Common Pitfalls:

Deadlocks due to incorrect semaphore ordering; missed signals; failing to bound the buffer or protect access with mutual exclusion.

Final Answer:

all of the above