Big O

Big O notation is used to describe the performance or complexity of an algorithm. It specifically represents the upper bound of the time or space complexity as the input size increases. Common complexities include O(1) (constant time), O(n) (linear time), O(log n) (logarithmic time), and O(n^2) (quadratic time).

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