eBay·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

eBay coding round, one algorithmic problem the whole session. Not a brutal interview but the question had enough edge cases to trip you up if you weren't careful with your indexing.

Questions Asked (1)

Given an integer array, find the longest contiguous subarray of even length where the sum of the first half equals the sum of the second half. Return the length or the subarray itself.

Algorithms & Data Structures

Author's notes

I jumped straight to brute force and the interviewer let me run with it for a bit before nudging me toward prefix sums.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and edge cases, then propose a solution using prefix sums and a hash map to track differences between prefix sums at even indices. Explain how to find the longest subarray by storing the earliest occurrence of each difference and updating the maximum length when a match is found.

Pro tip: Mention that the problem can be solved in O(n) time with O(n) space, and discuss how to handle negative numbers and large inputs efficiently. Also, note that returning the subarray itself requires tracking indices, not just lengths.

1. Clarify the problem

Ask clarifying questions: Is the array guaranteed to have at least one such subarray? Should we return the length or the subarray? Are there constraints on time/space complexity? Can the array contain negative numbers?

2. Define the approach

Explain that we can use prefix sums and a hash map. For a subarray from i to j (even length), the condition is sum(i..i+k-1) = sum(i+k..j) where k = (j-i+1)/2. This can be transformed into a condition on prefix sums at even indices.

3. Derive the key insight

Show that if we define an array B where B[t] = A[2t] - A[2t+1] (or similar), the condition becomes that the sum of B over a range is zero. Then use prefix sums of B and a hash map to find the longest zero-sum subarray.

4. Walk through an example

Pick a small array (e.g., [1,2,3,0,6] or [1,2,1,2]) and demonstrate how the algorithm works step by step, including how to track the earliest index for each prefix sum difference.

5. Analyze complexity and edge cases

State that the time complexity is O(n) and space is O(n). Discuss edge cases: no such subarray, all zeros, negative numbers, and how to return the subarray itself by storing start and end indices.

Key Points to Mention

Prefix sums and their role in reducing the problem to finding equal sums.
Hash map to store the first occurrence of each prefix sum difference (or transformed prefix sum).
Handling even-length constraint by considering pairs of elements or indices.
Time and space complexity: O(n) time, O(n) space.
Edge cases: empty array, no valid subarray, all zeros, negative numbers.
How to reconstruct the subarray if required, by storing indices in the hash map.

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