Summary Time Complexity and Big O Notation

Time Complexity and Big O Notation (with notes)


So the input size didn't increase and the runtime of the algorithms didn't increase
either .No , it doesn't depend on the size of the input . When we ask questions like
as the input will increase, Then the runtime will change as per what? And after that
Now you will go to aunty's house You will be treated. Consider there are different
routes to come and go.

is the algorithm that runs in constant time . K1 n to the power 0+k2+k3+k4 This
time is required in algo 2 .The sentence is: Run time of it, there are some things
that we will recite. Because we won't constantly use our brains again and again, as
we see Big O of 1 it is constant. Now, come here and listen to another story. If we
do an analysis of the first algorithm, If I do T algo1 Then what will happen here?
And along with consider that game is of L3 kb. If the game is of N kb then how
much time will you need? The sentence is: Run time of it, there are some things
that we will recite.There are polynomial algorithms and there are exponential
algorithms and there are logarithmic algorithms and there are exponential
functions and there are logarithmic functions. There are also algorithms that are
not linear in time.