Is Longest Common Subsequence Between Sorted Arrays easy or hard?

The problem is typically classified as Medium. The logic is straightforward once you recognize the counting pattern, but the challenge is identifying that the subsequence requirement simplifies to finding values present in every sorted array.

Longest Common Subsequence Between Sorted Arrays Python/Java solution

In Python, use a dictionary or collections.Counter to track frequencies while iterating through arrays. In Java, use a HashMap . Increment counts for each element and collect numbers whose count equals the number of arrays.

How to solve Longest Common Subsequence Between Sorted Arrays in O(n)?

Traverse every array and maintain a hash map that counts how many arrays contain each number. Since each array is strictly increasing, you increment the count once per element. After processing all arrays, collect numbers whose frequency equals the number of arrays. The runtime becomes linear in the total number of elements.

What is the best approach for Longest Common Subsequence Between Sorted Arrays?

The most efficient approach uses a hash map counting technique. Iterate through each array and increment the frequency of every number. Any value whose count equals the total number of arrays appears in all arrays. This runs in O(T) time where T is the total number of elements across arrays, with O(U) extra space for unique values.

Is Longest Common Subsequence Between Sorted Arrays asked at Google/Amazon/Meta?

Problems involving array intersection, hash map counting, and multi-array processing frequently appear in interviews at companies like Amazon, Google, and Meta. This specific problem tests recognition of counting patterns and efficient use of hash tables.

What data structure is used in Longest Common Subsequence Between Sorted Arrays?

The optimal solution uses a hash map (dictionary) to count occurrences of each number across arrays. Arrays are iterated sequentially, and the hash map stores how many arrays contain each value.

What is the time complexity of Longest Common Subsequence Between Sorted Arrays?

Using the optimal counting approach, the time complexity is O(T), where T is the total number of elements across all arrays. Each element is processed exactly once. Space complexity is O(U) for the hash map storing unique values.

Description Hints 3 Solution Video 7:28

1940. Longest Common Subsequence Between Sorted Arrays

Medium81.3% acceptance1 companyPremium elsewhere, free here

Given an array of integer arrays arrays where each arrays[i] is sorted in strictly increasing order, return an integer array representing the longest common subsequence among all the arrays.

A subsequence is a sequence that can be derived from another sequence by deleting some elements (possibly none) without changing the order of the remaining elements.

Example 1:

Input: arrays = [[1,3,4],
                 [1,4,7,9]]
Output: [1,4]
Explanation: The longest common subsequence in the two arrays is [1,4].

Example 2:

Input: arrays = [[2,3,6,8],
                 [1,2,3,5,6,7,10],
                 [2,3,4,6,9]]
Output: [2,3,6]
Explanation: The longest common subsequence in all three arrays is [2,3,6].

Example 3:

Input: arrays = [[1,2,3,4,5],
                 [6,7,8]]
Output: []
Explanation: There is no common subsequence between the two arrays.

Constraints:

2 <= arrays.length <= 100
1 <= arrays[i].length <= 100
1 <= arrays[i][j] <= 100
arrays[i] is sorted in strictly increasing order.

Asked at 1 company

Google

Topics

Hints open one at a time

Hint 1

Fix one array.

Hint 2

Choose the next array and get the common elements.

Hint 3

Use the common elements as the new fixed array and keep merging with the rest of the arrays.

7:28

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