Is Find Common Elements Between Two Arrays easy or hard?

LeetCode classifies this problem as Easy. The main idea is recognizing that repeated membership checks should use a hash set instead of nested loops. Once you apply the set approach, the implementation is straightforward.

Find Common Elements Between Two Arrays Python/Java solution

Most implementations build sets from both arrays and perform membership checks. Python uses the built‑in set type, Java uses HashSet, C++ uses unordered_set, and JavaScript uses Set. The algorithm logic remains the same across languages with O(n + m) time complexity.

How to solve Find Common Elements Between Two Arrays in O(n)?

Use a hash set for fast lookups. Insert elements of nums1 into one set and nums2 into another. Then iterate through each array and check if the current value exists in the opposite set. Each lookup is O(1) on average, so the total runtime becomes O(n + m).

What is the best approach for Find Common Elements Between Two Arrays?

The hash set approach is the most efficient solution. Convert both arrays into sets and check membership while iterating through the original arrays. Hash lookups run in average O(1) time, giving an overall complexity of O(n + m) with O(n + m) extra space.

Is Find Common Elements Between Two Arrays asked at Google/Amazon/Meta?

Array and hash table lookup problems like this appear frequently in technical interviews at companies such as Amazon, Google, and Meta. The problem tests your ability to recognize when a hash set can replace repeated linear searches.

What data structure is used in Find Common Elements Between Two Arrays?

The key data structure is a hash set. It stores elements from one array and allows constant‑time membership checks while scanning the other array. This reduces repeated comparisons and improves the runtime from O(n * m) to O(n + m).

What is the time complexity of Find Common Elements Between Two Arrays?

The optimal solution runs in O(n + m) time, where n and m are the lengths of the two arrays. Each array is processed once, and membership checks use constant‑time hash lookups. A brute force solution requires O(n * m) time due to nested comparisons.

Description Hints 2 Solution Video 9:00

2956. Find Common Elements Between Two Arrays

Easy84.5% acceptance5 companies

You are given two integer arrays nums1 and nums2 of sizes n and m, respectively. Calculate the following values:

answer1 : the number of indices i such that nums1[i] exists in nums2.
answer2 : the number of indices i such that nums2[i] exists in nums1.

Return [answer1,answer2].

Example 1:

Input: nums1 = [2,3,2], nums2 = [1,2]

Output: [2,1]

Explanation:

Example 2:

Input: nums1 = [4,3,2,3,1], nums2 = [2,2,5,2,3,6]

Output: [3,4]

Explanation:

The elements at indices 1, 2, and 3 in nums1 exist in nums2 as well. So answer1 is 3.

The elements at indices 0, 1, 3, and 4 in nums2 exist in nums1. So answer2 is 4.

Example 3:

Input: nums1 = [3,4,2,3], nums2 = [1,5]

Output: [0,0]

Explanation:

No numbers are common between nums1 and nums2, so answer is [0,0].

Constraints:

n == nums1.length
m == nums2.length
1 <= n, m <= 100
1 <= nums1[i], nums2[i] <= 100

Asked at 5 companies

Yandex

Google Amazon Meta Bloomberg

Topics

Array Hash Table

Hints open one at a time

Hint 1

Since the constraints are small, you can use brute force to solve the problem.

Hint 2

For each element i in nums1, iterate over all elements of nums2 to find if it occurs.

9:00

Still stuck?Read 3 approaches, or watch a walkthrough.

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1class Solution:
2    def findIntersectionValues(self, nums1: List[int], nums2: List[int]) -> List[int]:
3        

Starter codePython 3Spaces: 4

Examples

Case 1Case 2Case 3

Input

[2,3,2]
[1,2]

Input

[4,3,2,3,1]
[2,2,5,2,3,6]

Input

[3,4,2,3]
[1,5]

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