How do you solve Find Common Elements Between Two Arrays on LeetCode?

Find Common Elements Between Two Arrays (LeetCode #2956) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n + m) time complexity and O(n + m) space complexity. Key insight: Using a HashSet allows for faster lookups compared to nested loops.

What is the brute force solution for Find Common Elements Between Two Arrays?

The brute force approach for Find Common Elements Between Two Arrays is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach checks each element of the first array against every element of the second array. This is straightforward and works well given the small constraints. The optimal Optimal Solution approach improves this to O(n + m).

What algorithm or data structure is used to solve Find Common Elements Between Two Arrays?

Find Common Elements Between Two Arrays uses the following concepts: Array, Hash Table. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Find Common Elements Between Two Arrays?

Always consider the constraints and choose an appropriate approach. Explain your thought process clearly when discussing your solution. Practice dry-running your code with different examples to ensure correctness.

What are common mistakes when solving Find Common Elements Between Two Arrays?

Not using a HashSet for quick lookups, leading to inefficient solutions. Overlooking edge cases, such as arrays with no common elements.

#2956

Find Common Elements Between Two Arrays

Easy

ArrayHash TableHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n + m)
Space	O(1)	O(n + m)

💡

Intuition

Time O(n + m)Space O(n + m)

Using a HashSet allows us to quickly check for the existence of elements, reducing the time complexity significantly. This is like having a quick reference guide that tells you if an item is present without having to search through a list.

⚙️

Algorithm

6 steps

1Step 1: Create a HashSet from nums2 for fast look-up.
2Step 2: Initialize counters answer1 and answer2 to 0.
3Step 3: For each element in nums1, check if it exists in the HashSet. If it does, increment answer1.
4Step 4: Create a HashSet from nums1 for the second check.
5Step 5: For each element in nums2, check if it exists in the second HashSet. If it does, increment answer2.
6Step 6: Return [answer1, answer2].

solution.py8 lines

1# Full working Python code
2
3def find_common_elements(nums1, nums2):
4    set_nums2 = set(nums2)
5    answer1 = sum(1 for num in nums1 if num in set_nums2)
6    set_nums1 = set(nums1)
7    answer2 = sum(1 for num in nums2 if num in set_nums1)
8    return [answer1, answer2]

ℹ

Complexity note: The time complexity is O(n + m) because we create sets from both arrays and then check membership, which is efficient. The space complexity is O(n + m) due to the storage of two sets.

1Using a HashSet allows for faster lookups compared to nested loops.
2Understanding the trade-off between time and space complexity is crucial.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.