O Notation
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Keep it simple!
Just think of the Big-O as a way to express the performance of the algorythm. That performance will depend on the number of elements the algorythm is handeling = n.
An example, when you have to make a sum. You need one statement for the first addition, one statement for the second addition, and so on... So the performance will be linear with the number of elements = O(n).
Imagine a sort algorythm, which is very smart, and for each element of handles it automatically shortens the sort for the next element. This will be logarithmic with the number of elements = O(log(n)).
Or a complex formula with parameters, and with each extra parameter, the execution time multiplies. This will be exponential = O(10^n).
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