Asymptotic Growth Rate

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Big-0h notation allows us to describe the growth rate of functions. Used to compare the runtime of algorithms.

$T(n)$ ist he preciserunning time whereas $O(n^2)$ is the program's asymptotic running time.

Interchange by supresing constant factors and dropping lower-orderterms. It is an approximation!

• Suppress constant factors as they are dependent on how the algorithm is expressed.
• Ignore lower-order terms as they are irrelevant when the input gets arbitrarily large

O(n) describes a group of realtime functions that all exhibit a rutime that lineary grows as the size of input increases. All function in a particular group are conisdered to have the same (asymptotic efficiency).

Big-Oh notation: $O(f(n))$ is a set (or class)of cuntions taht grow no faster than $f(n)$.