Meta·Software Engineer·Onsite - Coding / Algorithms·Senior

SeniorPrefer not to say

Apr 2026

Summary

Meta SWE coding round with one meaty simulation problem. The question looks straightforward on the surface but the complexity discussion at the end is where things get interesting.

Questions Asked (1)

Given a non-negative integer array, simulate a repeated process: find the leftmost non-zero element, use it as a pivot value, walk rightward subtracting it from each subsequent element unless that element is smaller than the pivot, then add the pivot to a running total and repeat until no non-zeros remain. Return the total. Also discuss time complexity and potential optimizations over the naive simulation.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The simulation itself wasn't too bad to code up once I nailed down the pivot behavior.

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AI HintsAI Generated

Suggested Approach

First, clarify the problem with an example and edge cases, then walk through the naive simulation step-by-step while tracking the total. After confirming correctness, analyze the time complexity and propose optimizations such as using a monotonic stack or segment tree to avoid redundant scans.

Pro tip: Interviewers at Meta value clean, bug-free code and the ability to identify patterns—practice explaining how the process resembles a monotonic stack problem where each element's contribution is determined by the next smaller element.

1. Clarify and Example

Restate the problem in your own words, ask clarifying questions about edge cases (empty array, all zeros, large values), and walk through a small example to ensure understanding.

2. Naive Simulation

Describe the straightforward simulation: repeatedly scan for the leftmost non-zero, subtract it from subsequent elements until a smaller element is found, add to total, and repeat. Analyze its time complexity, typically O(n^2) in the worst case.

3. Identify Inefficiencies

Point out that the naive approach re-scans elements many times. Note that each element can be subtracted multiple times by different pivots, leading to redundant work.

4. Optimization Strategy

Propose an optimized approach using a monotonic stack to track elements and their contributions. Explain how each element's value is subtracted by the nearest smaller element to its left, and how to compute the total in O(n) time.

5. Complexity and Trade-offs

Compare the naive O(n^2) simulation with the optimized O(n) stack-based solution. Discuss space complexity and when the naive approach might be acceptable (e.g., small n).

Key Points to Mention

The process is equivalent to summing each element's value multiplied by the number of times it acts as a pivot or is subtracted.
A monotonic stack can efficiently find the next smaller element to the left, which determines how many times an element is subtracted.
Time complexity: naive O(n^2), optimized O(n) with O(n) space.
Edge cases: empty array, all zeros, strictly increasing/decreasing arrays, large integers causing overflow.
Potential alternative optimizations: segment tree for range updates, or two-pointer technique if applicable.
Communication: explain your thought process clearly and test with examples.

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