ORTANT: The penalty scheme for this question is 50, 100%. ect one: a. Time complexity = O(n) b. Time complexity = O(n^2) c. Time complexity = O(2n) d. Time complexity = O(log n) e. Time complexity = O(n log n) heck
ORTANT: The penalty scheme for this question is 50, 100%. ect one: a. Time complexity = O(n) b. Time complexity = O(n^2) c. Time complexity = O(2n) d. Time complexity = O(log n) e. Time complexity = O(n log n) heck
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
Related questions
Question
![For the following function, select the most appropriate time complexity in terms of n:
def rate(n):
i = 0
total = 0
while in:
j= n
while j > 1:
total + j
j // = 2
i += 1
return total
IMPORTANT: The penalty scheme for this question is 50, 100%.
Select one:
O a. Time complexity = O(n)
O b.
Time complexity = O(n^2)
O c.
Time complexity = O(2n)
O d.
Time complexity = O(log n)
e. Time complexity = O(n log n)
Check](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fda0be02e-f777-40ec-8b6c-8836435acb5a%2Fe69c72d8-8f4f-4c13-a87c-aee8dc17905f%2Fiqfpv9c_processed.png&w=3840&q=75)
Transcribed Image Text:For the following function, select the most appropriate time complexity in terms of n:
def rate(n):
i = 0
total = 0
while in:
j= n
while j > 1:
total + j
j // = 2
i += 1
return total
IMPORTANT: The penalty scheme for this question is 50, 100%.
Select one:
O a. Time complexity = O(n)
O b.
Time complexity = O(n^2)
O c.
Time complexity = O(2n)
O d.
Time complexity = O(log n)
e. Time complexity = O(n log n)
Check
Expert Solution
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Step 1
Solution - The correct option of the above code is b i.e the code run with the complexity of O(n^2).
As the i loop equals to 0 so total also = 0,
while i<n ;j=n here the complexity run with O(n)
Next coming to while j>1 ; total with increment equals to 1
It runs for n times and linear increment its complexity is O(n).
It is also rub for every i loop so its complexity is O(n2).
Time complexity = O(n2).
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