Big O Notation
A more theoretical way of comparing one algorithm to another is called Big O Notation. There are couple of rules with the notation to remember:
- Constant are ignored
- Smaller components are ignored For Example:
O(500*n) -> O(n), the constant value which is 500 is replaced with 1.
O(999999)->O(1), the constant value which is 999999 is replaced with 1.
O(10*n^2 +5n +20) ->O(n^2), the constant value 10 is replaced with 1 and the added smaller components are ignored.
O(n*n)->O(n^2), no constant or added value.
O(nlog(n) + 30000n)
->O(n*log(n)), the added smaller components are ignored.
O(1) or {Constant time}: The algorithm is not dependent on a variable dataset i.e regardless of the input size, the runtime of the algorithm will not increase beyond the constant size.
to be continued....