In the book Programming Interviews Exposed it says that the complexity of the program below is O(N), but I don't understand how this is possible. Can someone explain why this is?
int var = 2;
for (int i = 0; i < N; i++) {
for (int j = i+1; j < N; j *= 2) {
var += var;
}
}
You need a bit of math to see that. The inner loop iterates Θ(1 + log [N/(i+1)])
times (the 1 +
is necessary since for i >= N/2
, [N/(i+1)] = 1
and the logarithm is 0, yet the loop iterates once). j
takes the values (i+1)*2^k
until it is at least as large as N
, and
(i+1)*2^k >= N <=> 2^k >= N/(i+1) <=> k >= log_2 (N/(i+1))
using mathematical division. So the update j *= 2
is called ceiling(log_2 (N/(i+1)))
times and the condition is checked 1 + ceiling(log_2 (N/(i+1)))
times. Thus we can write the total work
N-1 N
∑ (1 + log (N/(i+1)) = N + N*log N - ∑ log j
i=0 j=1
= N + N*log N - log N!
Now, Stirling's formula tells us
log N! = N*log N - N + O(log N)
so we find the total work done is indeed O(N)
.
Outer loop runs n
times. Now it all depends on the inner loop.
The inner loop now is the tricky one.
Lets follow:
i=0 --> j=1 ---> log(n) iterations
...
...
i=(n/2)-1 --> j=n/2 ---> 1 iteration.
i=(n/2) --> j=(n/2)+1 --->1 iteration.
i > (n/2) ---> 1 iteration
(n/2)-1 >= i > (n/4) ---> 2 iterations
(n/4) >= i > (n/8) ---> 3 iterations
(n/8) >= i > (n/16) ---> 4 iterations
(n/16) >= i > (n/32) ---> 5 iterations
(n/2)*1 + (n/4)*2 + (n/8)*3 + (n/16)*4 + ... + [n/(2^i)]*i
N-1
n*∑ [i/(2^i)] =< 2*n
i=0
--> O(n)
@Daniel Fischer's answer is correct.
I would like to add the fact that this algorithm's exact running time is as follows:
Which means: