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Algorithm analysis: divide & conquer theory

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

Can we divide problem into more than 2 sub problems?

a)

Yes

b)

No

2.

Divide & Conquer strategy is a guaranteed to be better than brute force.

a)

true

b)

false

3.

Strategy is a (a)   to solve a problem.

4.

In divide & conquer strategy, problems are solved (a)   .

5.

To use divide & conquer strategy, we must know how to ________ our problem and ________ the solutions.

(a)  

6.

When using technique 'A', we divide a problem into subproblems. When the solution to each subproblem is ready, we 'combine' the results from the subproblems to solve the main problem. What might be the 'A' here?

a)

Divide Technique

b)

Divide and Conquer Technique

c)

Split and Combine Technique

d)

Combine Technique

7.

divide and conqure approach solves subproblems recursively.

a)

False

b)

True

8.

What is the time complexity of the Merge Sort algorithm, which is an example of the Divide and Conquer technique, for sorting an array of n elements?

a)

O(n)

b)

O(log n)

c)

O(nlogn)

d)

O( n2n^2 )

9.

Which of the following are the advantages of using the Divide and Conquer technique?

a)

It can reduce the time complexity of an algorithm

b)

It can simplify the implementation of an algorithm

c)

It can reduce the space complexity of an algorithm

d)

It can always guarantee the optimal solution to a problem

10.

Referring to the master theorem –>T(n) = aT(n/b) + f(n), what could be the value for a here?

a)

1

b)

2

c)

3

d)

4