TikTok·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

TikTok data engineer interview with a coding problem focused on array partitioning. Pretty lean on context but the problem itself had some interesting edge cases worth thinking through.

Questions Asked (1)

Given an array of integers, split it into subarrays such that each subarray has an equal sum.

Algorithms & Data Structures

Author's notes

My first instinct was prefix sums, which got me somewhere but I fumbled explaining the partition logic cleanly.

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AI HintsAI Generated

Suggested Approach

First, clarify the problem constraints and edge cases, then propose an efficient algorithm that computes the target sum and greedily partitions the array while validating each segment. Discuss time and space complexity, and consider alternative approaches if the problem allows non-contiguous subarrays.

Pro tip: Always confirm whether the subarrays must be contiguous and whether the split must use all elements; these details drastically change the solution and show you think about real-world ambiguity.

1. Clarify Requirements

Ask if subarrays must be contiguous, if all elements must be used, and if the number of subarrays is fixed or flexible. Also check for constraints like array size and value range.

2. Handle Edge Cases

Check if the total sum is divisible by the desired number of subarrays (if fixed) or if the target sum is achievable. Handle empty array, zeros, and negative numbers appropriately.

3. Design Algorithm

For contiguous subarrays with equal sum, compute the target sum (total sum divided by k, if k is given) and greedily accumulate elements until the target is reached, then start a new subarray. For non-contiguous, consider subset sum or DP approaches.

4. Analyze Complexity

State the time complexity (e.g., O(n) for greedy contiguous) and space complexity (O(1) extra space). Discuss trade-offs if using DP.

5. Test with Examples

Walk through a few examples, including edge cases, to verify the algorithm works and to demonstrate correctness.

Key Points to Mention

Contiguity requirement: whether subarrays must be contiguous or can be any subset.
Total sum divisibility: if splitting into k parts, total sum must be divisible by k.
Greedy accumulation: for contiguous, accumulate until target sum is reached.
Handling zeros and negative numbers: they can affect the greedy approach.
Time and space complexity: O(n) time and O(1) space for the greedy contiguous approach.
Alternative approaches: dynamic programming or backtracking for non-contiguous or variable number of subarrays.

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