Using big O notation to give upper bounds on time and space complexity of algorithms, what is the worst- case run time of the pseudo-code below? Algorithm MultAdd(A,n) Input: Array A storing integers and of size n > 1000 sum <-0 for c <-0 to 1000 do if A[c] < 0 then for k<-0 to n - 1 do sum <- sum + k * A[c]

Computer Networking: A Top-Down Approach (7th Edition)
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Author:James Kurose, Keith Ross
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Soru 5
Using big O notation to give upper bounds on time and space complexity of algorithms, what is the worst-
Henüz
case run time of the pseudo-code below?
cevaplanmadı
Algorithm MultAdd(A,n)
20,00 üzerinden
işaretlenmiş
Input: Array A storing integers and of size n > 1000
P Soruyu
sum <-0
işaretle
for c <-0 to 1000 do
if A[c] < 0 then
for k<-0 to n - 1 do
sum <- sum + k * A[c]
O a. O(N°logN)
O b. O(N)
Oc. O(3N)
O d. O(1)
O e. O(N?)
Transcribed Image Text:Soru 5 Using big O notation to give upper bounds on time and space complexity of algorithms, what is the worst- Henüz case run time of the pseudo-code below? cevaplanmadı Algorithm MultAdd(A,n) 20,00 üzerinden işaretlenmiş Input: Array A storing integers and of size n > 1000 P Soruyu sum <-0 işaretle for c <-0 to 1000 do if A[c] < 0 then for k<-0 to n - 1 do sum <- sum + k * A[c] O a. O(N°logN) O b. O(N) Oc. O(3N) O d. O(1) O e. O(N?)
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