Pattern Design Concurrency Patterns 3

Question 1

The Pipeline concurrency pattern organizes computation as:

Accepted Answer

A series of processing stages where each stage transforms data and passes it downstream to the next stage

Answer

A single thread that processes all tasks one by one in strict arrival order

Answer

A pool of threads competing to pick up tasks from a single shared work queue

Answer

Multiple threads reading from the same immutable data source simultaneously

Question 2

Which technique used in concurrent data structures divides the structure into independent segments, each guarded by its own lock, to reduce contention?

Accepted Answer

Lock Striping

Answer

Using a single global lock to protect the entire data structure

Answer

Using a read-write lock to allow multiple concurrent readers

Answer

Eliminating all locks by making the structure immutable

Question 3

The Compare-and-Swap (CAS) atomic operation is the fundamental building block for which class of concurrent algorithms?

Accepted Answer

Lock-free and wait-free algorithms that avoid traditional mutex locks

Answer

Lock-based synchronization using monitor objects

Answer

Thread pool scheduling and task dispatch algorithms

Answer

Event-driven reactive programming models

Question 4

In the Proactor pattern, how are asynchronous operations handled?

Accepted Answer

The application initiates them and registers completion handlers that are invoked automatically when operations finish

Answer

The OS completes them with no involvement from the application layer

Answer

They are dispatched synchronously in a fixed-size thread pool with no callbacks

Answer

The application initiates them and then blocks until they complete synchronously

Question 5

Which concurrency pattern allows a thread to safely read data that another thread might be modifying, by working on a private copy rather than the shared original?

Accepted Answer

Copy-on-Write

Answer

Singleton

Answer

Template Method

Answer

Factory Method

Question 6

The LMAX Disruptor pattern improves concurrent throughput primarily by:

Accepted Answer

Replacing traditional blocking queues with a pre-allocated ring buffer to eliminate lock contention and GC pressure

Answer

Spawning additional threads automatically when queue depth exceeds a threshold

Answer

Prioritizing high-value financial transactions over low-value background tasks

Answer

Using a hierarchical locking scheme where each lock level prevents deadlocks

Question 7

In concurrent programming, the Immutability pattern prevents data races by:

Accepted Answer

Constructing objects whose state can never change after initialization, eliminating the need for synchronization entirely

Answer

Protecting all shared objects with a single application-wide lock

Answer

Scheduling threads in time slices so they never truly run at the same moment

Answer

Creating a defensive copy of each object before handing it to another thread