What are the different types of Big O notation?

What are the different types of Big O notation?

Big O notation is used to describe 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 a different growth rate.

Can you explain what O(1) means?

O(1), or constant time complexity, means that the algorithm's performance is constant and does not change with the size of the input data. For example, accessing an element in an array by index.

What about O(n log n)? When is it used?

O(n log n) is commonly seen in efficient sorting algorithms like mergesort and heapsort. It indicates that the time complexity grows in relation to the input size multiplied by the logarithm of the input size.

Are there any algorithms that have O(n^2) complexity?

Yes, algorithms like bubble sort and selection sort have O(n^2) complexity. They become inefficient for large datasets due to their quadratic growth.