LeetCode #2032 — EASY

Two Out of Three

Build confidence with an intuition-first walkthrough focused on array fundamentals.

The Problem

Problem Statement

Given three integer arrays nums1, nums2, and nums3, return a distinct array containing all the values that are present in at least two out of the three arrays. You may return the values in any order.

Example 1:

Input: nums1 = [1,1,3,2], nums2 = [2,3], nums3 = [3]
Output: [3,2]
Explanation: The values that are present in at least two arrays are:
- 3, in all three arrays.
- 2, in nums1 and nums2.

Example 2:

Input: nums1 = [3,1], nums2 = [2,3], nums3 = [1,2]
Output: [2,3,1]
Explanation: The values that are present in at least two arrays are:
- 2, in nums2 and nums3.
- 3, in nums1 and nums2.
- 1, in nums1 and nums3.

Example 3:

Input: nums1 = [1,2,2], nums2 = [4,3,3], nums3 = [5]
Output: []
Explanation: No value is present in at least two arrays.

Constraints:

1 <= nums1.length, nums2.length, nums3.length <= 100
1 <= nums1[i], nums2[j], nums3[k] <= 100

Step 01

Brute Force Baseline

Problem summary: Given three integer arrays nums1, nums2, and nums3, return a distinct array containing all the values that are present in at least two out of the three arrays. You may return the values in any order.

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: Array · Hash Map · Bit Manipulation

Example 1

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

Example 2

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

Example 3

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

Step 02

Core Insight

What unlocks the optimal approach

What data structure can we use to help us quickly find whether an element belongs in an array?
Can we count the frequencies of the elements in each array?

Interview move: turn each hint into an invariant you can check after every iteration/recursion step.

Step 03

Algorithm Walkthrough

Iteration Checklist

Define state (indices, window, stack, map, DP cell, or recursion frame).
Apply one transition step and update the invariant.
Record answer candidate when condition is met.
Continue until all input is consumed.

Use the first example testcase as your mental trace to verify each transition.

Step 04

Edge Cases

Minimum Input

Single element / shortest valid input

Validate boundary behavior before entering the main loop or recursion.

Duplicates & Repeats

Repeated values / repeated states

Decide whether duplicates should be merged, skipped, or counted explicitly.

Extreme Constraints

Upper-end input sizes

Re-check complexity target against constraints to avoid time-limit issues.

Invalid / Corner Shape

Empty collections, zeros, or disconnected structures

Handle special-case structure before the core algorithm path.

Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #2032: Two Out of Three
class Solution {
    public List<Integer> twoOutOfThree(int[] nums1, int[] nums2, int[] nums3) {
        int[] s1 = get(nums1), s2 = get(nums2), s3 = get(nums3);
        List<Integer> ans = new ArrayList<>();
        for (int i = 1; i <= 100; ++i) {
            if (s1[i] + s2[i] + s3[i] > 1) {
                ans.add(i);
            }
        }
        return ans;
    }

    private int[] get(int[] nums) {
        int[] s = new int[101];
        for (int num : nums) {
            s[num] = 1;
        }
        return s;
    }
}

// Accepted solution for LeetCode #2032: Two Out of Three
func twoOutOfThree(nums1 []int, nums2 []int, nums3 []int) (ans []int) {
	get := func(nums []int) (s [101]int) {
		for _, v := range nums {
			s[v] = 1
		}
		return
	}
	s1, s2, s3 := get(nums1), get(nums2), get(nums3)
	for i := 1; i <= 100; i++ {
		if s1[i]+s2[i]+s3[i] > 1 {
			ans = append(ans, i)
		}
	}
	return
}

# Accepted solution for LeetCode #2032: Two Out of Three
class Solution:
    def twoOutOfThree(
        self, nums1: List[int], nums2: List[int], nums3: List[int]
    ) -> List[int]:
        s1, s2, s3 = set(nums1), set(nums2), set(nums3)
        return [i for i in range(1, 101) if (i in s1) + (i in s2) + (i in s3) > 1]

// Accepted solution for LeetCode #2032: Two Out of Three
use std::collections::HashSet;
impl Solution {
    pub fn two_out_of_three(nums1: Vec<i32>, nums2: Vec<i32>, nums3: Vec<i32>) -> Vec<i32> {
        let mut count = vec![0; 101];
        nums1
            .into_iter()
            .collect::<HashSet<i32>>()
            .iter()
            .for_each(|&v| {
                count[v as usize] += 1;
            });
        nums2
            .into_iter()
            .collect::<HashSet<i32>>()
            .iter()
            .for_each(|&v| {
                count[v as usize] += 1;
            });
        nums3
            .into_iter()
            .collect::<HashSet<i32>>()
            .iter()
            .for_each(|&v| {
                count[v as usize] += 1;
            });
        let mut ans = Vec::new();
        count.iter().enumerate().for_each(|(i, v)| {
            if *v >= 2 {
                ans.push(i as i32);
            }
        });
        ans
    }
}

// Accepted solution for LeetCode #2032: Two Out of Three
function twoOutOfThree(nums1: number[], nums2: number[], nums3: number[]): number[] {
    const count = new Array(101).fill(0);
    new Set(nums1).forEach(v => count[v]++);
    new Set(nums2).forEach(v => count[v]++);
    new Set(nums3).forEach(v => count[v]++);
    const ans = [];
    count.forEach((v, i) => {
        if (v >= 2) {
            ans.push(i);
        }
    });
    return ans;
}

Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Custom checkpoints (one per line)

Press Step or Run All to begin.

Step 07

Complexity Analysis

Time

O(n_1 + n_2 + n_3)

Space

O(n_1 + n_2 + n_3)

Approach Breakdown

SORT + SCAN

O(n log n) time

O(n) space

Sort the array in O(n log n), then scan for the missing or unique element by comparing adjacent pairs. Sorting requires O(n) auxiliary space (or O(1) with in-place sort but O(n log n) time remains). The sort step dominates.

BIT MANIPULATION

O(n) time

O(1) space

Bitwise operations (AND, OR, XOR, shifts) are O(1) per operation on fixed-width integers. A single pass through the input with bit operations gives O(n) time. The key insight: XOR of a number with itself is 0, which eliminates duplicates without extra space.

Shortcut: Bit operations are O(1). XOR cancels duplicates. Single pass → O(n) time, O(1) space.

Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Off-by-one on range boundaries

Wrong move: Loop endpoints miss first/last candidate.

Usually fails on: Fails on minimal arrays and exact-boundary answers.

Fix: Re-derive loops from inclusive/exclusive ranges before coding.

Mutating counts without cleanup

Wrong move: Zero-count keys stay in map and break distinct/count constraints.

Usually fails on: Window/map size checks are consistently off by one.

Fix: Delete keys when count reaches zero.