Given two sequence P and Q of numbers. The task is to find Longest Common Subsequence of two sequences if we are allowed to change at most k element in first sequence to any value.
Examples:
Input : P = { 8, 3 }
Q = { 1, 3 }
K = 1
Output : 2
If we change first element of first
sequence from 8 to 1, both sequences
become same.
Input : P = { 1, 2, 3, 4, 5 }
Q = { 5, 3, 1, 4, 2 }
K = 1
Output : 3
By changing first element of first
sequence to 5 to get the LCS ( 5, 3, 4 }.
The idea is to use Dynamic Programming. Define a 3D matrix dp[][][], where dp[i][j][k] defines the Longest Common Subsequence for the first i numbers of first array, first j number of second array when we are allowed to change at max k number in the first array.
Therefore, recursion will look like
If P[i] != Q[j],
dp[i][j][k] = max(dp[i - 1][j][k],
dp[i][j - 1][k],
dp[i - 1][j - 1][k - 1] + 1)
If P[i] == Q[j],
dp[i][j][k] = max(dp[i - 1][j][k],
dp[i][j - 1][k],
dp[i - 1][j - 1][k] + 1)
Below is The implementation of this approach:
C++
// CPP program to find LCS of two arrays with // k changes allowed in first array. #include <bits/stdc++.h> using namespace std; #define MAX 10 // Return LCS with at most k changes allowed. int lcs(int dp[MAX][MAX][MAX], int arr1[], int n, int arr2[], int m, int k) { // If at most changes is less than 0. if (k < 0) return -1e7; // If any of two array is over. if (n < 0 || m < 0) return 0; // Making a reference variable to dp[n][m][k] int& ans = dp[n][m][k]; // If value is already calculated, return // that value. if (ans != -1) return ans; // calculating LCS with no changes made. ans = max(lcs(dp, arr1, n - 1, arr2, m, k), lcs(dp, arr1, n, arr2, m - 1, k)); // calculating LCS when array element are same. if (arr1[n-1] == arr2[m-1]) ans = max(ans, 1 + lcs(dp, arr1, n - 1, arr2, m - 1, k)); // calculating LCS with changes made. ans = max(ans, 1 + lcs(dp, arr1, n - 1, arr2, m - 1, k - 1)); return ans; } // Driven Program int main() { int k = 1; int arr1[] = { 1, 2, 3, 4, 5 }; int arr2[] = { 5, 3, 1, 4, 2 }; int n = sizeof(arr1) / sizeof(arr1[0]); int m = sizeof(arr2) / sizeof(arr2[0]); int dp[MAX][MAX][MAX]; memset(dp, -1, sizeof(dp)); cout << lcs(dp, arr1, n, arr2, m, k) << endl; return 0; } |
Java
// Java program to find LCS of two arrays with // k changes allowed in first array. class GFG { static int MAX = 10; // Return LCS with at most k changes allowed. static int lcs(int[][][] dp, int[] arr1, int n, int[] arr2, int m, int k) { // If at most changes is less than 0. if (k < 0) return -10000000; // If any of two array is over. if (n < 0 || m < 0) return 0; // Making a reference variable to dp[n][m][k] int ans = dp[n][m][k]; // If value is already calculated, return // that value. if (ans != -1) return ans; try { // calculating LCS with no changes made. ans = Math.max(lcs(dp, arr1, n - 1, arr2, m, k), lcs(dp, arr1, n, arr2, m - 1, k)); // calculating LCS when array element are same. if (arr1[n - 1] == arr2[m - 1]) ans = Math.max(ans, 1 + lcs(dp, arr1, n - 1, arr2, m - 1, k)); // calculating LCS with changes made. ans = Math.max(ans, 1 + lcs(dp, arr1, n - 1, arr2, m - 1, k - 1)); } catch (Exception e) { } return ans; } // Driver Code public static void main(String[] args) { int k = 1; int[] arr1 = { 1, 2, 3, 4, 5 }; int[] arr2 = { 5, 3, 1, 4, 2 }; int n = arr1.length; int m = arr2.length; int[][][] dp = new int[MAX][MAX][MAX]; for (int i = 0; i < MAX; i++) for (int j = 0; j < MAX; j++) for (int l = 0; l < MAX; l++) dp[i][j][l] = -1; System.out.println(lcs(dp, arr1, n, arr2, m, k)); } } // This code is contributed by // sanjeev2552 |
Python3
# Python3 program to find LCS of two arrays # with k changes allowed in the first array. MAX = 10 # Return LCS with at most k changes allowed. def lcs(dp, arr1, n, arr2, m, k): # If at most changes is less than 0. if k < 0: return -(10 ** 7) # If any of two array is over. if n < 0 or m < 0: return 0 # Making a reference variable to dp[n][m][k] ans = dp[n][m][k] # If value is already calculated, # return that value. if ans != -1: return ans # calculating LCS with no changes made. ans = max(lcs(dp, arr1, n - 1, arr2, m, k), lcs(dp, arr1, n, arr2, m - 1, k)) # calculating LCS when array element are same. if arr1[n-1] == arr2[m-1]: ans = max(ans, 1 + lcs(dp, arr1, n - 1, arr2, m - 1, k)) # calculating LCS with changes made. ans = max(ans, lcs(dp, arr1, n - 1, arr2, m - 1, k - 1)) return ans # Driven Program if __name__ == "__main__": k = 1 arr1 = [1, 2, 3, 4, 5] arr2 = [5, 3, 1, 4, 2] n = len(arr1) m = len(arr2) dp = [[[-1 for i in range(MAX)] for j in range(MAX)] for k in range(MAX)] print(lcs(dp, arr1, n, arr2, m, k)) # This code is contributed by Rituraj Jain |
C#
// C# program to find LCS of two arrays with // k changes allowed in first array. using System; class GFG { static int MAX = 10; // Return LCS with at most // k changes allowed. static int lcs(int[,,] dp, int[] arr1, int n, int[] arr2, int m, int k) { // If at most changes is less than 0. if (k < 0) return -10000000; // If any of two array is over. if (n < 0 || m < 0) return 0; // Making a reference variable // to dp[n,m,k] int ans = dp[n, m, k]; // If value is already calculated, // return that value. if (ans != -1) return ans; try { // calculating LCS with no changes made. ans = Math.Max(lcs(dp, arr1, n - 1, arr2, m, k), lcs(dp, arr1, n, arr2, m - 1, k)); // calculating LCS when // array element are same. if (arr1[n - 1] == arr2[m - 1]) ans = Math.Max(ans, 1 + lcs(dp, arr1, n - 1, arr2, m - 1, k)); // calculating LCS with changes made. ans = Math.Max(ans, 1 + lcs(dp, arr1, n - 1, arr2, m - 1, k - 1)); } catch (Exception e) { } return ans; } // Driver Code public static void Main(String[] args) { int k = 1; int[] arr1 = { 1, 2, 3, 4, 5 }; int[] arr2 = { 5, 3, 1, 4, 2 }; int n = arr1.Length; int m = arr2.Length; int[,,] dp = new int[MAX, MAX, MAX]; for (int i = 0; i < MAX; i++) for (int j = 0; j < MAX; j++) for (int l = 0; l < MAX; l++) dp[i, j, l] = -1; Console.WriteLine(lcs(dp, arr1, n, arr2, m, k)); } } // This code is contributed by PrinciRaj1992 |
Output:
3
Time Complexity: O(N*M*K).
This article is contributed by Anuj Chauhan. If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
Attention reader! Don’t stop learning now. Get hold of all the important DSA concepts with the DSA Self Paced Course at a student-friendly price and become industry ready.
Recommended Posts:
- Longest common subsequence with permutations allowed
- Longest Common Subsequence | DP-4
- Printing Longest Common Subsequence
- Longest Common Increasing Subsequence (LCS + LIS)
- LCS (Longest Common Subsequence) of three strings
- C++ Program for Longest Common Subsequence
- Java Program for Longest Common Subsequence
- Python Program for Longest Common Subsequence
- Minimum cost to make Longest Common Subsequence of length k
- Longest Common Subsequence | DP using Memoization
- Edit distance and LCS (Longest Common Subsequence)
- Length of longest common subsequence containing vowels
- Length of longest common prime subsequence from two given arrays
- Count common subsequence in two strings
- Print all longest common sub-sequences in lexicographical order
- Longest Repeated Subsequence
- Print Longest Palindromic Subsequence
- Shortest Common Supersequence
- Printing Shortest Common Supersequence
- Shortest Uncommon Subsequence

