algorithm

Edit Distance Dynamic Algorithm

Minimum Edits required to convert string 1 to string 2

The problem statement is like if we are given two string str1 and str2 then how many minimum number of operations can be performed on the str1 that it gets converted to str2.The Operations can be:

  1. Insert
  2. Remove
  3. Replace

For Example

Input: str1 = "geek", str2 = "gesek"
Output: 1
We only need to insert s in first string

Input: str1 = "march", str2 = "cart"
Output: 3
We need to replace m with c and remove character c and then replace h with t

To solve this problem we will use a 2D array dp[n+1][m+1] where n is the length of the first string and m is the length of the second string. For our example, if str1 is azcef and str2 is abcdef then our array will be dp[6][7]and our final answer will be stored at dp[5][6].

          (a) (b) (c) (d) (e) (f)
     +---+---+---+---+---+---+---+
     | 0 | 1 | 2 | 3 | 4 | 5 | 6 |
     +---+---+---+---+---+---+---+
  (a)| 1 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+
  (z)| 2 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+
  (c)| 3 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+
  (e)| 4 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+
  (f)| 5 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+

For dp[1][1] we have to check what can we do to convert a into a.It will be 0.For dp[1][2] we have to check what can we do to convert a into ab.It will be 1 because we have to insert b.So after 1st iteration our array will look like

          (a) (b) (c) (d) (e) (f)
     +---+---+---+---+---+---+---+
     | 0 | 1 | 2 | 3 | 4 | 5 | 6 |
     +---+---+---+---+---+---+---+
  (a)| 1 | 0 | 1 | 2 | 3 | 4 | 5 |
     +---+---+---+---+---+---+---+
  (z)| 2 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+
  (c)| 3 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+
  (e)| 4 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+
  (f)| 5 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+ 

For iteration 2

For dp[2][1] we have to check that to convert az to a we need to remove z, hence dp[2][1] will be 1.Similary for dp[2][2] we need to replace z with b, hence dp[2][2] will be 1.So after 2nd iteration our dp[][] array will look like.

         (a) (b) (c) (d) (e) (f)
     +---+---+---+---+---+---+---+
     | 0 | 1 | 2 | 3 | 4 | 5 | 6 |
     +---+---+---+---+---+---+---+
  (a)| 1 | 0 | 1 | 2 | 3 | 4 | 5 |
     +---+---+---+---+---+---+---+
  (z)| 2 | 1 | 1 | 2 | 3 | 4 | 5 |
     +---+---+---+---+---+---+---+
  (c)| 3 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+
  (e)| 4 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+
  (f)| 5 |   |   |   |   |   |   |
     +---+---+---+---+---+---+---+

So our formula will look like

if characters are same
    dp[i][j] = dp[i-1][j-1];
else
    dp[i][j] = 1 + Min(dp[i-1][j], dp[i][j-1], dp[i-1][j-1])

After last iteration our dp[][] array will look like

          (a) (b) (c) (d) (e) (f)
     +---+---+---+---+---+---+---+
     | 0 | 1 | 2 | 3 | 4 | 5 | 6 |
     +---+---+---+---+---+---+---+
  (a)| 1 | 0 | 1 | 2 | 3 | 4 | 5 |
     +---+---+---+---+---+---+---+
  (z)| 2 | 1 | 1 | 2 | 3 | 4 | 5 |
     +---+---+---+---+---+---+---+
  (c)| 3 | 2 | 2 | 1 | 2 | 3 | 4 |
     +---+---+---+---+---+---+---+
  (e)| 4 | 3 | 3 | 2 | 2 | 2 | 3 |
     +---+---+---+---+---+---+---+
  (f)| 5 | 4 | 4 | 2 | 3 | 3 | 3 |
     +---+---+---+---+---+---+---+

Implementation in Java

public int getMinConversions(String str1, String str2){
    int dp[][] = new int[str1.length()+1][str2.length()+1];
    for(int i=0;i<=str1.length();i++){
        for(int j=0;j<=str2.length();j++){
            if(i==0)
                dp[i][j] = j;
            else if(j==0)
                dp[i][j] = i;
            else if(str1.charAt(i-1) == str2.charAt(j-1))
                dp[i][j] = dp[i-1][j-1];
            else{
                dp[i][j] = 1 + Math.min(dp[i-1][j], Math.min(dp[i][j-1], dp[i-1][j-1]));
            }
        }
    }
    return dp[str1.length()][str2.length()];
}

Time Complexity

O(n^2)

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