Question 11 The time complexity of Merge sort can be represented using recurrence T(n) = 2T(n/2) + n = (n log n). O True O False

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
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Question 11
The time complexity of Merge sort can be represented using recurrence T(n) = 2T(n/2) + n = (n log n).
O True
O False
Question 12
A MCM problem is defined as p = <10, 20, 30>, then the cost of this MCM problem is 10*20*30= 6,000.
O True
O False
Question 13
If f(n)= Theta(g(n)), then f(n) = Omega(g(n)) and f(n) = O(g(n)).
If everything displays correctly, it should be like
If f(n) = (g(n)), then f(n) = (g(n)) and f(n) = O(g(n)).
O True
O False
Question 14
For the 0/1 Knapsack problem, if we have n items, and the sack has a capacity of w, then there is always just one
optimal solution and the dynamic programming approach we introduced in class would find the solution.
O True
O False
Question 15
Programming paradigms are algorithms presented using a spoken language such as English.
O True
O False
Transcribed Image Text:Question 11 The time complexity of Merge sort can be represented using recurrence T(n) = 2T(n/2) + n = (n log n). O True O False Question 12 A MCM problem is defined as p = <10, 20, 30>, then the cost of this MCM problem is 10*20*30= 6,000. O True O False Question 13 If f(n)= Theta(g(n)), then f(n) = Omega(g(n)) and f(n) = O(g(n)). If everything displays correctly, it should be like If f(n) = (g(n)), then f(n) = (g(n)) and f(n) = O(g(n)). O True O False Question 14 For the 0/1 Knapsack problem, if we have n items, and the sack has a capacity of w, then there is always just one optimal solution and the dynamic programming approach we introduced in class would find the solution. O True O False Question 15 Programming paradigms are algorithms presented using a spoken language such as English. O True O False
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