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Dynamic Programming in Data Structures
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Consider the 3×3 matrix {{2,1,-3},{6,3,4},{-2,3,0}}. What is the sum of the elements of the maximum sum rectangle?

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You are given infinite coins of denominations 5, 7, 9. Which of the following sum CANNOT be achieved using these coins?

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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;
}

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What is the value stored in sum[4] after the following program is executed?
#include<stdio.h>
int max_num(int a,int b)
{
      if(a> b)
	  return a;
      return b;
}
int maximum_subarray_sum(int *arr, int len)
{
      int sum[len], idx;
      sum[0] = arr[0];
      for(idx = 1; idx < len; idx++)
	   sum[idx] = max_num(sum[idx - 1] + arr[idx], arr[idx]);
      int mx = sum[0];
      for(idx = 0; idx < len; idx++)
	  if(sum[idx] > mx)
	      mx =sum[idx];
      return mx;
}
int main()
{
      int arr[] = {-2, 14, 11, -13, 10, -5, 11, -6, 3, -5},len = 10;
      int ans = maximum_subarray_sum(arr, len);
      printf("%d",ans);
      return 0;
}

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What is the value stored in arr[3][3] when the following code is executed?
#include<stdio.h>
#include<string.h>
int max_num(int a, int b)
{
      if(a > b)
        return a;
      return b;
}
int lps(char *str1)
{
      int i,j,len;
      len = strlen(str1);
      char str2[len + 1];
      strcpy(str2, str1);
      strrev(str2);
      int arr[len + 1][len + 1];
      for(i = 0; i <= len; i++)
          arr[i][0] = 0;
      for(i = 0; i <= len; i++)
          arr[0][i] = 0;
      for(i = 1; i <= len; i++)
      {
          for(j = 1; j <= len; j++)
          {
                if(str1[i-1] == str2[j - 1])
                    arr[i][j] = 1 + arr[i - 1][j - 1];
                else
                    arr[i][j] = max_num(arr[i - 1][j], arr[i][j - 1]);
          }
      }
      return arr[len][len];
}
int main()
{
      char str1[] = "ababcdabba";
      int ans = lps(str1);
      printf("%d",ans);
      return 0;
}

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What is the time complexity of the following dynamic programming implementation of the balanced partition problem where "n" is the number of elements and "sum" is their sum?
#include<stdio.h>
int balanced_partition(int *arr, int len)
{
     int sm = 0, i, j;
     for(i = 0;i < len; i++)
      sm += arr[i];
     if(sm % 2 != 0)
        return 0;
     int ans[sm/2 + 1][len + 1];
     for(i = 0; i <= len; i++)
      ans[0][i] = 1;
     for(i = 1; i <= sm/2; i++)
      ans[i][0] = 0;
     for(i = 1; i <= sm/2; i++)
     {
         for(j = 1;j <= len; j++)
         {
             ans[i][j] = ans[i][j-1];
             if(i >= arr[j - 1])
                ans[i][j] = ans[i][j] || ans[i - arr[j - 1]][j - 1];
         }
     }
     return ans[sm/2][len];
}
int main()
{
     int arr[] = {3, 4, 5, 6, 7, 1}, len = 6;
     int ans = balanced_partition(arr,len);
     if(ans == 0)
       printf("false");
     else
       printf("true");
     return 0;
}

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What is the time complexity of the brute force algorithm used to find the longest common subsequence?

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Consider the strings "PQRSTPQRS" and "PRATPBRQRPS". What is the length of the longest common subsequence?

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Consider the following code snippet:
int max_sum_rectangle(int arr[][3],int row,int col)
{
      int left, right, tmp[row], mx_sm = INT_MIN, idx, val;
      for(left = 0; left < col; left++)
      {
           for(right = left; right < col; right++)
           {
               if(right == left)
               {
                   for(idx = 0; idx < row; idx++)
                     tmp[idx] = arr[idx][right];
               }
               else
               {
                   for(idx = 0; idx < row; idx++)
                      tmp[idx] += arr[idx][right];
               }
               val = kadane_algo(tmp,row);
               if(val > mx_sm)
                  ______;
           }
      }
      return mx_sm;
}
Which of the following lines should be inserted to complete the above code?

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What is the space complexity of the following dynamic programming implementation to find the longest palindromic subsequence where the length of the string is n?
#include<stdio.h>
#include<string.h>
int max_num(int a, int b)
{
      if(a > b)
        return a;
      return b;
}
int lps(char *str1)
{
      int i,j,len;
      len = strlen(str1);
      char str2[len + 1];
      strcpy(str2, str1);
      strrev(str2);
      int arr[len + 1][len + 1];
      for(i = 0; i <= len; i++)
          arr[i][0] = 0;
      for(i = 0; i <= len; i++)
          arr[0][i] = 0;
      for(i = 1; i <= len; i++)
      {
          for(j = 1; j <= len; j++)
          {
               if(str1[i-1] == str2[j - 1])
                   arr[i][j] = 1 + arr[i - 1][j - 1];
               else
                   arr[i][j] = max_num(arr[i - 1][j], arr[i][j - 1]);
          }
      }
      return arr[len][len];
}
int main()
{
     char str1[] = "ababcdabba";
     int ans = lps(str1);
     printf("%d",ans);
     return 0;
}

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Which of the following methods can be used to solve the edit distance problem?

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What is the time complexity of the following dynamic programming implementation of the edit distance problem where "m" and "n" are the lengths of two strings?
#include<stdio.h>
#include<string.h>
int get_min(int a, int b)
{
      if(a < b)
        return a;
      return b;
}
int edit_distance(char *s1, char *s2)
{
     int len1,len2,i,j,min;
     len1 = strlen(s1);
     len2 = strlen(s2);
     int arr[len1 + 1][len2 + 1];
     for(i = 0;i <= len1; i++)
       arr[i][0] = i;
     for(i = 0; i <= len2; i++)
       arr[0][i] = i;
     for(i = 1; i <= len1; i++)
     {
         for(j = 1; j <= len2; j++)
         {
               min = get_min(arr[i-1][j],arr[i][j-1]) + 1;
               if(s1[i - 1] == s2[j - 1])
               {
                    if(arr[i-1][j-1] < min)
                       min = arr[i-1][j-1];
               }
               else
               {
                     if(arr[i-1][j-1] + 1 < min)
                         min = arr[i-1][j-1] + 1;
               }
                arr[i][j] = min;
         }
     }
     return arr[len1][len2];
}
int main()
{
     char s1[] = "abcd", s2[] = "defg";
     int ans = edit_distance(s1, s2);
     printf("%d",ans);
     return 0;
}

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What is the output of the following program?
#include<stdio.h>
#include<limits.h>
int min_jump(int *arr, int len)
{
      int j, idx, jumps[len];
      jumps[len - 1] = 0;
      for(idx = len - 2; idx >= 0; idx--)
      {	
	  int tmp_min = INT_MAX;
	  for(j = 1; j <= arr[idx] && idx + j < len; j++)
	  {
	        if(jumps[idx + j] + 1 < tmp_min)
		  tmp_min = jumps[idx + j] + 1;
	  }
	  jumps[idx] = tmp_min;
      }
      return jumps[0];
}
int main()
{
      int arr[] ={9, 9, 9, 9, 9, 9, 9, 9, 9},len = 9;
      int ans = min_jump(arr,len);
      printf("%d\n",ans);
      return 0;
}

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What is the time complexity of the following for loop method used to compute the nth fibonacci term?
int fibo(int n)
    if n == 0
       return 0 
    else
       prevFib = 0
       curFib = 1
       for i : 1 to n-1
           nextFib = prevFib + curFib
	   prevFib = curFib
           curFib = nextFib
       return curFib

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For which of the following inputs would Kadane's algorithm produce a WRONG output?

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Which of the following methods can be used to find the nth Catalan number?

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What is the space complexity of the following dynamic programming implementation used to find the length of the longest increasing subsequence?
#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;
}

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Which of the following problems should be solved using dynamic programming?

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Consider the following recursive implementation:
#include<stdio.h>
#include<limits.h>
int min_jumps(int *arr, int strt, int end)
{
     int idx;
     if(strt == end)
	return 0;
     if(arr[strt] == 0) // jump cannot be made
	return INT_MAX;
     int min = INT_MAX;
     for(idx = 1; idx <= arr[strt] && strt + idx <= end; idx++)
     {
	  int jumps = min_jumps(____,____,____) + 1;
	  if(jumps < min)
	      min  = jumps;
     }
     return min;
}
int main()
{
     int arr[] ={1, 3, 5, 8, 9, 2, 6, 7, 6},len = 9;
     int ans = min_jumps(arr, 0, len-1);
     printf("%d\n",ans);
     return 0;
}
Which of these arguments should be passed by the min_jumps function represented by the blanks?

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What is the output of the following code?
#include<stdio.h>
#include<string.h>
int max_num(int a, int b)
{
      if(a > b)
         return a;
      return b;
}
int lcs(char *str1, char *str2)
{
      int i,j,len1,len2;
      len1 = strlen(str1);
      len2 = strlen(str2);
      int arr[len1 + 1][len2 + 1];
      for(i = 0; i <= len1; i++)
          arr[i][0] = 0;
      for(i = 0; i <= len2; i++)
          arr[0][i] = 0;
      for(i = 1; i <= len1; i++)
      {
          for(j = 1; j <= len2; j++)
          {
              if(str1[i-1] == str2[j - 1])
                  arr[i][j] = 1 + arr[i - 1][j - 1];
              else
                  arr[i][j] = max_num(arr[i - 1][j], arr[i][j - 1]);
          }
      }
      return arr[len1][len2];
}
int main()
{
      char str1[] = "hbcfgmnapq", str2[] = "cbhgrsfnmq";
      int ans = lcs(str1,str2);
      printf("%d",ans);
      return 0;
}

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