Longest common subarray in the given two arrays

Difficulty Level : Medium
Last Updated : 25 Jan, 2021

Given two arrays A[] and B[] of N and M integers respectively, the task is to find the maximum length of equal subarray or the longest common subarray between the two given array.

Examples:

Input: A[] = {1, 2, 8, 2, 1}, B[] = {8, 2, 1, 4, 7}
Output: 3
Explanation:
The subarray that is common to both arrays are {8, 2, 1} and the length of the subarray is 3.
Input: A[] = {1, 2, 3, 2, 1}, B[] = {8, 7, 6, 4, 7}
Output: 0
Explanation:
There is no such subarrays which are equal in the array A[] and B[].

Naive Approach: The idea is to generate all the subarrays of the two given array A[] and B[] and find the longest matching subarray. This solution is exponential in terms of time complexity.
Time Complexity: O(2^N+M), where N is the length of the array A[] and M is the length of the array B[].

Efficient Approach:
The efficient approach is to use Dynamic Programming(DP). This problem is the variation of the Longest Common Subsequence(LCS).
Let the input sequences are A[0..n-1] and B[0..m-1] of lengths m & n respectively. Following is the recursive implementation of the equal subarrays:

Since common subarray of A[] and B[] must start at some index i and j such that A[i] is equals to B[j]. Let dp[i][j] be the longest common subarray of A[i…] and B[j…].
Therefore, for any index i and j, if A[i] is equals to B[j], then dp[i][j] = dp[i+1][j+1] + 1.
The maximum of all the element in the array dp[][] will give the maximum length of equal subarrays.

For Example:
If the given array A[] = {1, 2, 8, 2, 1} and B[] = {8, 2, 1, 4, 7}. If the characters match at index i and j for the array A[] and B[] respectively, then dp[i][j] will be updated as 1 + dp[i+1][j+1].
Below is the updated dp[][] table for the given array A[] and B[].

Below is the implementation of the above approach:

C++

// C++ program to DP approach
// to above solution
#include <bits/stdc++.h>
using namespace std;
 
// Function to find the maximum
// length of equal subarray
int FindMaxLength(int A[], int B[], int n, int m)
{
 
    // Auxillary dp[][] array
    int dp[n + 1][m + 1];
    for (int i = 0; i <= n; i++)
        for (int j = 0; j <= m; j++)
            dp[i][j] = 0;
 
    // Updating the dp[][] table
    // in Bottom Up approach
    for (int i = n - 1; i >= 0; i--)
    {
        for (int j = m - 1; j >= 0; j--)
        {
            // If A[i] is equal to B[i]
            // then dp[j][i] = dp[j + 1][i + 1] + 1
            if (A[i] == B[j])
                dp[j][i] = dp[j + 1][i + 1] + 1;
        }
    }
    int maxm = 0;
 
    // Find maximum of all the values
    // in dp[][] array to get the
    // maximum length
    for (int i = 0; i < n; i++)
    {
        for (int j = 0; j < m; j++)
        {
            // Update the length
            maxm = max(maxm, dp[i][j]);
        }
    }
 
    // Return the maximum length
    return maxm;
}
 
// Driver Code
int main()
{
    int A[] = { 1, 2, 8, 2, 1 };
    int B[] = { 8, 2, 1, 4, 7 };
 
    int n = sizeof(A) / sizeof(A[0]);
    int m = sizeof(B) / sizeof(B[0]);
 
    // Function call to find
    // maximum length of subarray
    cout << (FindMaxLength(A, B, n, m));
}
 
// This code is contributed by chitranayal

Java

// Java program to DP approach
// to above solution
class GFG
{
    // Function to find the maximum
    // length of equal subarray
    static int FindMaxLength(int A[], int B[], int n, int m)
    {
 
        // Auxillary dp[][] array
        int[][] dp = new int[n + 1][m + 1];
        for (int i = 0; i <= n; i++)
            for (int j = 0; j <= m; j++)
                dp[i][j] = 0;
 
        // Updating the dp[][] table
        // in Bottom Up approach
        for (int i = n - 1; i >= 0; i--)
        {
            for (int j = m - 1; j >= 0; j--)
            {
                // If A[i] is equal to B[i]
                // then dp[j][i] = dp[j + 1][i + 1] + 1
                if (A[i] == B[j])
                    dp[j][i] = dp[j + 1][i + 1] + 1;
            }
        }
        int maxm = 0;
 
        // Find maximum of all the values
        // in dp[][] array to get the
        // maximum length
        for (int i = 0; i < n; i++)
        {
            for (int j = 0; j < m; j++)
            {
                // Update the length
                maxm = Math.max(maxm, dp[i][j]);
            }
        }
 
        // Return the maximum length
        return maxm;
    }
 
    // Driver Code
    public static void main(String[] args)
    {
        int A[] = { 1, 2, 8, 2, 1 };
        int B[] = { 8, 2, 1, 4, 7 };
 
        int n = A.length;
        int m = B.length;
 
        // Function call to find
        // maximum length of subarray
        System.out.print(FindMaxLength(A, B, n, m));
    }
}
 
// This code is contributed by PrinciRaj1992

Python

# Python program to DP approach
# to above solution
 
# Function to find the maximum
# length of equal subarray
 
 
def FindMaxLength(A, B):
    n = len(A)
    m = len(B)
 
    # Auxillary dp[][] array
    dp = [[0 for i in range(n + 1)] for i in range(m + 1)]
 
    # Updating the dp[][] table
    # in Bottom Up approach
    for i in range(n - 1, -1, -1):
        for j in range(m - 1, -1, -1):
 
            # If A[i] is equal to B[i]
            # then dp[j][i] = dp[j + 1][i + 1] + 1
            if A[i] == B[j]:
                dp[j][i] = dp[j + 1][i + 1] + 1
    maxm = 0
 
    # Find maximum of all the values
    # in dp[][] array to get the
    # maximum length
    for i in dp:
        for j in i:
 
            # Update the length
            maxm = max(maxm, j)
 
    # Return the maximum length
    return maxm
 
 
# Driver Code
if __name__ == '__main__':
    A = [1, 2, 8, 2, 1]
    B = [8, 2, 1, 4, 7]
 
    # Function call to find
    # maximum length of subarray
    print(FindMaxLength(A, B))

C#

// C# program to DP approach
// to above solution
using System;
 
class GFG
{
    // Function to find the maximum
    // length of equal subarray
    static int FindMaxLength(int[] A, int[] B, int n, int m)
    {
 
        // Auxillary [,]dp array
        int[, ] dp = new int[n + 1, m + 1];
        for (int i = 0; i <= n; i++)
            for (int j = 0; j <= m; j++)
                dp[i, j] = 0;
 
        // Updating the [,]dp table
        // in Bottom Up approach
        for (int i = n - 1; i >= 0; i--)
        {
            for (int j = m - 1; j >= 0; j--)
            {
                // If A[i] is equal to B[i]
                // then dp[j, i] = dp[j + 1, i + 1] + 1
                if (A[i] == B[j])
                    dp[j, i] = dp[j + 1, i + 1] + 1;
            }
        }
        int maxm = 0;
 
        // Find maximum of all the values
        // in [,]dp array to get the
        // maximum length
        for (int i = 0; i < n; i++) {
            for (int j = 0; j < m; j++) {
 
                // Update the length
                maxm = Math.Max(maxm, dp[i, j]);
            }
        }
 
        // Return the maximum length
        return maxm;
    }
 
    // Driver Code
    public static void Main(String[] args)
    {
        int[] A = { 1, 2, 8, 2, 1 };
        int[] B = { 8, 2, 1, 4, 7 };
 
        int n = A.Length;
        int m = B.Length;
 
        // Function call to find
        // maximum length of subarray
        Console.Write(FindMaxLength(A, B, n, m));
    }
}
 
// This code is contributed by PrinciRaj1992

Output

Time Complexity: O(N*M), where N is the length of array A[] and M is the length of array B[].

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