Illumio·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

Interviewed at Illumio for a software engineer role and got a coding question that was basically a Two Sum variant but with a catch: the input was unsorted and you couldn't sort it either.

Questions Asked (1)

Given an unsorted array of integers, find two numbers that sum to a target value. Sorting the array is not allowed.

Algorithms & Data Structures

Author's notes

Looks like Two Sum at first glance, but the no-sorting constraint forces you to think about it differently.

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AI HintsAI Generated

Suggested Approach

Use a hash map to store each element's complement (target minus current value) as you iterate through the array. For each element, check if it exists in the map; if so, return the pair, otherwise add its complement to the map. This achieves O(n) time and O(n) space without sorting.

Pro tip: Clarify upfront whether the array can contain duplicates or if multiple pairs exist, and mention that the hash map approach handles these cases naturally. Also, briefly discuss trade-offs with the two-pointer approach if sorting were allowed, showing awareness of constraints.

1. Clarify requirements and constraints

Ask about input size, duplicates, negative numbers, and whether exactly one solution exists. Confirm that sorting is not allowed and that O(n) time is expected.

2. Choose the optimal data structure

Select a hash map (dictionary) to store values and their indices, enabling O(1) lookups for complements. Explain why this avoids sorting and achieves linear time.

3. Iterate and check complements

Loop through the array; for each number, compute its complement (target - num). If the complement exists in the map, return the pair; otherwise, store the current number and its index.

4. Handle edge cases and return result

Consider cases like no solution, multiple solutions, or duplicate values. Return the indices or values as required, and discuss time/space complexity.

Key Points to Mention

Time complexity: O(n) with a single pass using a hash map.
Space complexity: O(n) for the hash map, which is optimal without sorting.
Handling duplicates: the hash map approach naturally supports duplicates by storing the first occurrence or updating as needed.
Alternative approach: two-pointer technique if sorting were allowed, but it's not, so hash map is preferred.
Edge cases: empty array, no solution, multiple solutions, negative numbers.
Trade-offs: hash map uses extra space but is faster; brute force is O(n^2) and not acceptable.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.