adplus-dvertising

Welcome to the Dynamic Programming MCQs Page

Dive deep into the fascinating world of Dynamic Programming with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Dynamic Programming, a crucial aspect of Data Structures and Algorithms. In this section, you will encounter a diverse range of MCQs that cover various aspects of Dynamic Programming, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Data Structures and Algorithms.

frame-decoration

Check out the MCQs below to embark on an enriching journey through Dynamic Programming. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Data Structures and Algorithms.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Dynamic Programming. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Dynamic Programming MCQs | Page 6 of 22

Q51.
Find the longest increasing subsequence for the given sequence:
{10, -10, 12, 9, 10, 15, 13, 14}
Discuss
Answer: (d).{-10, 9, 10, 13, 14}
Q52.
Find the length of the longest increasing subsequence for the given sequence:
{-10, 24, -9, 35, -21, 55, -41, 76, 84}

a.

5

b.

4

c.

3

d.

6

Discuss
Answer: (d).6
Q53.
For any given sequence, there will ALWAYS be a unique increasing subsequence with the longest length.
Discuss
Answer: (b).False
Q54.
The number of increasing subsequences with the longest length for the given sequence are:
{10, 9, 8, 7, 6, 5}

a.

3

b.

4

c.

5

d.

6

Discuss
Answer: (d).6
Q55.
In the brute force implementation to find the longest increasing subsequence, all the subsequences of a given sequence are found. All the increasing subsequences are then selected and the length of the longest subsequence is found. What is the time complexity of this brute force implementation?
Discuss
Answer: (d).O(2^n)
Q56.
Complete the following dynamic programming implementation of the longest increasing subsequence problem:
#include<stdio.h>
int longest_inc_sub(int *arr, int len)
{
      int i, j, tmp_max;
      int LIS[len];  // array to store the lengths of the longest increasing subsequence 
      LIS[0]=1;
      for(i = 1; i < len; i++)
      { 
           tmp_max = 0;
	   for(j = 0; j < i; j++)
	   {
	        if(arr[j] < arr[i])
	        {
		    if(LIS[j] > tmp_max)
		     ___________;  
	        }
           }
	   LIS[i] = tmp_max + 1;
      }
      int max = LIS[0];
      for(i = 0; i < len; i++)
	if(LIS[i] > max)
	   max = LIS[i];
      return max;
}
int main()
{
      int arr[] = {10,22,9,33,21,50,41,60,80}, len = 9;
      int ans = longest_inc_sub(arr, len);
      printf("%d",ans);
      return 0;
}
Discuss
Answer: (a).tmp_max = LIS[j].
Q57.
What is the output of the following program?
#include<stdio.h>
int longest_inc_sub(int *arr, int len)
{
      int i, j, tmp_max;
      int LIS[len];  // array to store the lengths of the longest increasing subsequence 
      LIS[0]=1;
      for(i = 1; i < len; i++)
      {
	    tmp_max = 0;
	    for(j = 0; j < i; j++)
	    {
	        if(arr[j] < arr[i])
	        {
		     if(LIS[j] > tmp_max)
		       tmp_max = LIS[j];
	        }
            }
	    LIS[i] = tmp_max + 1;
      }
      int max = LIS[0];
      for(i = 0; i < len; i++)
	  if(LIS[i] > max)
	      max = LIS[i];
      return max;
}
int main()
{
      int arr[] = {10,22,9,33,21,50,41,60,80}, len = 9;
      int ans = longest_inc_sub(arr, len);
      printf("%d",ans);
      return 0;
}

a.

3

b.

4

c.

5

d.

6

Discuss
Answer: (d).6
Q58.
What is the value stored in LIS[5] after the following program is executed?
#include<stdio.h>
int longest_inc_sub(int *arr, int len)
{
      int i, j, tmp_max;
      int LIS[len];  // array to store the lengths of the longest increasing subsequence 
      LIS[0]=1;
      for(i = 1; i < len; i++)
      {
	   tmp_max = 0;
	   for(j = 0; j < i; j++)
	   {
	        if(arr[j] < arr[i])
	        {
		     if(LIS[j] > tmp_max)
		     tmp_max = LIS[j];
	        }
	   }
	   LIS[i] = tmp_max + 1;
       }
      int max = LIS[0];
      for(i = 0; i < len; i++)
	 if(LIS[i] > max)
	     max = LIS[i];
      return max;
}
int main()
{
      int arr[] = {10,22,9,33,21,50,41,60,80}, len = 9;
      int ans = longest_inc_sub(arr, len);
      printf("%d",ans);
      return 0;
}

a.

2

b.

3

c.

4

d.

5

Discuss
Answer: (c).4
Q59.
Given a rod of length n and the selling prices of all pieces smaller than equal to n, find the most beneficial way of cutting the rod into smaller pieces. This problem is called the rod cutting problem. Which of these methods can be used to solve the rod cutting problem?
Discuss
Answer: (d).All of the mentioned
Q60.
You are given a rod of length 5 and the prices of each length are as follows:
length price

1 2

2 5

3 6

4 9

5 9

What is the maximum value that you can get after cutting the rod and selling the pieces?
Discuss
Answer: (c).12
Page 6 of 22

Suggested Topics

Are you eager to expand your knowledge beyond Data Structures and Algorithms? We've curated a selection of related categories that you might find intriguing.

Click on the categories below to discover a wealth of MCQs and enrich your understanding of Computer Science. Happy exploring!