What are the different types of Big O notation?

Can you explain the different types of Big O notation?

Sure! Big O notation describes the performance or complexity of an algorithm. The main types include O(1), O(log n), O(n), O(n log n), O(n^2), and O(2^n). Each represents how the runtime or space requirements grow as the input size increases.

What does O(1) mean?

O(1) denotes constant time complexity, meaning the algorithm's runtime does not change regardless of the input size.

And what about O(n log n)?

O(n log n) is often seen in efficient sorting algorithms like mergesort and heapsort, where the time grows in relation to the input size multiplied by the logarithm of the input size.

Can you give an example of O(n^2)?

Certainly! An example of O(n^2) is the bubble sort algorithm, where the time complexity increases quadratically with the number of elements being sorted.