I have an algorithm and I trace two different data sets through it$.$ The first input size is n $=100$ while the second is of size n $=10,000.$ It turns out both runs of the algorithm end up performing a constant number of comparisons to complete. What true statements can I make about the running time of this algorithm at this point $($even if those statements do not represent a tight bound$)?$ Select all that apply.

Question $3$ options:

A$)$

The worst$-$case running time of the algorithm is O$(2^$n$)$

B$)$

The average$-$case running time of this algorithm is $\backslash$Omega $(1).$

C$)$

The overall running time of the algorithm is $\backslash$theta $(1)$

D$)$

The overall running time of this algorithm is $\backslash$Theta $($n$).$