Big-O
Big-O is a mathematical notation used for describing the time and space complexity of an algorithm as the input size grows.
Ξ© = Best case Ξ = Average case O = Worst case
O (1)
Most efficient - as input grows, complexity remains constant
O(log n)
Very efficient - as input grows, complexity remains low, even for large input
Divide and Conquer
O (n)
Linear/Proportional - complexity grows inline with input
O (n log n)
O (n^2)
Loop within a loop
O (2^n)
O (n!)
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