What is Big O notation and why is it important?

What is Big O notation and why is it important?

Big O notation is a mathematical concept used to describe the performance or complexity of an algorithm. It specifically measures the worst-case scenario in terms of time or space as the input size grows.

Can you give me an example of how it works?

Sure! For example, if an algorithm takes a constant time to execute regardless of input size, we say it has a complexity of O(1). If it takes time proportional to the input size, like in a simple loop, it would be O(n).

What are some common complexities I should know?

Some common complexities include O(1) for constant time, O(log n) for logarithmic time, O(n) for linear time, O(n log n) for linearithmic time, and O(n^2) for quadratic time.

How does Big O notation help in choosing algorithms?

Big O notation helps in comparing the efficiency of different algorithms, allowing developers to choose the most suitable one based on the expected input size and performance requirements.