15. 3Sum
mediumAsked at Juniper NetworksFind all unique triplets that sum to zero. Juniper uses 3Sum to test whether candidates can compose sort + two-pointer cleanly and handle duplicate elimination — the same multi-pass filtering logic appears in prefix-list deduplication and routing policy intersection in network management software.
By Sam K., Founder, InterviewChamp.AI · Last verified
Source citations
Public interview reports confirming this problem appears in Juniper Networks loops.
- Glassdoor (2026-Q1)— Cited in Juniper SWE onsite reports as a classic medium-difficulty problem testing sort and two-pointer.
- Blind (2025-12)— Juniper threads list 3Sum as a go-to medium problem in technical interviews across multiple teams.
Problem
Given an integer array nums, return all the triplets [nums[i], nums[j], nums[k]] such that i != j, i != k, j != k, and nums[i] + nums[j] + nums[k] == 0. Notice that the solution set must not contain duplicate triplets.
Constraints
3 <= nums.length <= 3000−10^5 <= nums[i] <= 10^5
Examples
Example 1
nums = [-1,0,1,2,-1,-4][[-1,-1,2],[-1,0,1]]Explanation: Two unique triplets sum to zero.
Example 2
nums = [0,1,1][]Explanation: No triplet sums to zero.
Example 3
nums = [0,0,0][[0,0,0]]Explanation: Only one unique triplet.
Approaches
1. Sort + two pointers
Sort the array. For each element nums[i], use two pointers (left = i+1, right = n-1) to find pairs that sum to -nums[i]. Skip duplicates at each level.
- Time
- O(n²)
- Space
- O(1) excluding output
function threeSum(nums) {
nums.sort((a, b) => a - b);
const result = [];
for (let i = 0; i < nums.length - 2; i++) {
if (i > 0 && nums[i] === nums[i - 1]) continue; // skip duplicate i
let left = i + 1, right = nums.length - 1;
while (left < right) {
const sum = nums[i] + nums[left] + nums[right];
if (sum === 0) {
result.push([nums[i], nums[left], nums[right]]);
while (left < right && nums[left] === nums[left + 1]) left++;
while (left < right && nums[right] === nums[right - 1]) right--;
left++; right--;
} else if (sum < 0) {
left++;
} else {
right--;
}
}
}
return result;
}Tradeoff: O(n²) time, O(1) extra space. The canonical solution. Duplicate skipping is the subtle part — get it right at all three levels (i, left, right).
Juniper Networks-specific tips
Sorting first is the key insight — state it before writing code. The two-pointer sweep works because the sorted order lets you decide directionally whether to increase or decrease the running sum. Juniper interviewers will specifically probe the duplicate-skipping logic. Walk through nums = [-1,-1,0,1] step by step to show you handle the i-level duplicate correctly.
Common mistakes
- Forgetting to skip duplicates at the i level (i > 0 && nums[i] === nums[i-1]) — produces duplicate triplets.
- Skipping duplicates before pushing the result instead of after — misses the first occurrence of a valid triplet.
- Not advancing both pointers after finding a triplet — causes an infinite loop when duplicates exist.
- Using a Set of stringified arrays to deduplicate instead of pointer logic — correct but much slower.
Follow-up questions
An interviewer at Juniper Networks may pivot to one of these next:
- 4Sum (LC 18) — add one more loop and reduce to 3Sum.
- 3Sum Closest (LC 16) — find the triplet sum closest to a target.
- How would you extend to k-Sum for arbitrary k?
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FAQ
Why sort first?
Sorting enables the two-pointer technique (move left up, right down based on sum direction) and makes duplicate detection trivial by grouping equal values together.
What does the i > 0 guard on the duplicate skip do?
It prevents skipping the very first element (i=0). Without it, we would skip nums[0] before ever processing it.
Can we do better than O(n²)?
No known general algorithm does better than O(n²) for the exact triplet enumeration problem. O(n log n) for preprocessing (sort) does not help the output phase.