It is what describes and shows the growth rate of an algorithm along with the increase in the input value. The growth rate refers to how much resources it requires as the input values increases.
| Complexity | Name | What it Means | Example |
|---|---|---|---|
O(1) |
Constant Time | Takes the same time regardless of input size | Accessing an array element |
O(log n) |
Logarithmic Time | Runtime grows slowly as input size increases | Binary Search |
O(n) |
Linear Time | Runtime grows proportionally with input size | Looping through an array |
O(n log n) |
Log-Linear Time | Common in efficient sorting algorithms; slightly faster than linear | Merge Sort, Quick Sort |
O(n²) |
Quadratic Time | Runtime grows quadratically; inefficient for large inputs | Bubble Sort, Insertion Sort |
