Find the complexity of the following blocks of code or algorithm's description. [Note: your answer must show the steps that lead to your final answer] | 2) 1) count = 0 for i = 1 to n do for k = 1 to n do count = 1 for i = 1 to n do count += i for k = 1 to n do for (j = 2; j

Computer Networking: A Top-Down Approach (7th Edition)
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ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
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Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Question 4:
Find the complexity of the following blocks of code or algorithm's description.
[Note: your answer must show the steps that lead to your final answer]
1) count = 0
for i = 1 to n do
for k = 1 to n do
2)
for i = 1 to n do
count += i
count = 1
for (j = 2;j<n;j *= 2)
count = i +k + j;
for k = 1 to n do
count *= k
end for
k +=2
while j< n do
count +=j
j*= 2;
end while
The algorithm solves the problem
of size n by recursively solving
sub-problems of size n – 1, and
then combining the solutions in
Q(n) time.
end for
end for
3) The algorithm solves the problem of 4)
size n by dividing it into 64 sub-
problems of size n/8, recursively
solving each sub-problem, and then
combining the solutions in O(n?)
time
5) The algorithm solves the problem
by breaking it into 8 sub-problems
of 1/4 the scale, recursively solving
each sub-maze, and then
combining the solutions in linear
time
Transcribed Image Text:Question 4: Find the complexity of the following blocks of code or algorithm's description. [Note: your answer must show the steps that lead to your final answer] 1) count = 0 for i = 1 to n do for k = 1 to n do 2) for i = 1 to n do count += i count = 1 for (j = 2;j<n;j *= 2) count = i +k + j; for k = 1 to n do count *= k end for k +=2 while j< n do count +=j j*= 2; end while The algorithm solves the problem of size n by recursively solving sub-problems of size n – 1, and then combining the solutions in Q(n) time. end for end for 3) The algorithm solves the problem of 4) size n by dividing it into 64 sub- problems of size n/8, recursively solving each sub-problem, and then combining the solutions in O(n?) time 5) The algorithm solves the problem by breaking it into 8 sub-problems of 1/4 the scale, recursively solving each sub-maze, and then combining the solutions in linear time
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