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It's a system of symbols used to compare the execution time of algorithms (time complexity) or the memory space required for an operation (space complexity).

• O(1) The time of execution is always the same, like when the first element of an array is returned.
• O(N) The time of execution grow linearly, like when we process all the elements of an array.
• O(N^2) The time of execution is proportional to the square of the array size, like comparing each element with each other.
• O(2^N) The time of execution is exponential and grow very fast.
• O(logN) The time of execution grow very slowly, like in the case of a binary tree.
• O(n logN) This is the product of a linear and a logarithmic execution.