Big O notation is super important for understanding how queues and stacks work in linear data structures.

It helps us figure out how much time and space these structures will need, which lets us guess how well they will perform.

Time Complexity

• Stack Operations (Push, Pop): Both of these actions take $O(1)$ time. This means no matter how big the stack gets, they will always take the same amount of time to complete.

• Queue Operations (Enqueue, Dequeue): These also take $O(1)$ time. This makes queues really good for handling tasks quickly.

Space Complexity

• Both stacks and queues usually require $O(n)$ space, where $n$ is the number of items they hold.

Knowing about these complexities is very helpful. It can guide you in picking the best structure for your algorithm!