In computer science, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithm.
Big O: Big O notation is a mathematical notation that describes the limiting behavior of a function when the argument tends towards a particular value or infinity. To put it in a simple terms big O describes the performance of an algorithm.
Array
| Lookup by Index | O(1) |
| Lookup by Value | O(n) |
| Insert | O(n) |
| Delete | O(n) |
Linked List
| Lookup by value | O(n) |
| Lookup by Index | O(n) |
| Insert at the beginning | O(1) |
| Insert at the middle | O(n) |
| Insert at the end | O(1) |
| Delete at the beginning | O(1) |
| Delete at the middle | O(n) |
| Delete from the end | O(n) |
Stack
| push | O(1) |
| pop | O(1) |
| peek | O(1) |
| isEmpty | O(1) |
Queue
| Enqueue | O(1) |
| Dequeue | O(1) |
| Peek | O(1) |
| isEmpty | O(1) |
| isFull | O(1) |
