Walmart·Software Engineer·Online Assessment (OA)·Senior

SeniorPending

Apr 2026Remote

Summary

Took a timed online coding assessment for a company I really need to land, and the results were rough. The environment is barebones with no autocomplete, which after nearly two decades of working in real IDEs feels almost deliberately cruel. Four days out from the actual test and I'm not feeling great about it.

Questions Asked (1)

Solve the MissingInteger problem: given an array of integers, find the smallest positive integer that does not appear in the array.

Algorithms & Data Structures

Author's notes

Passed all the examples, which honestly lulled me into thinking I was fine.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., array size, value range, memory limits) and then propose an O(n) time and O(1) space solution using the array itself as a hash table. Explain the algorithm step-by-step, handle edge cases, and analyze time/space complexity.

Pro tip: Mention that you would first check if the array can be modified; if not, you might need a different approach, but in-place is often acceptable and demonstrates space optimization. Also, discuss potential integer overflow when using values as indices.

1. Clarify constraints and edge cases

Ask about array size, possible values (negative, zero, duplicates), and whether the array can be modified. Discuss edge cases like empty array, all negatives, or all positives up to n.

2. Propose an efficient algorithm

Describe the in-place hashing approach: iterate through the array, and for each positive integer within range, mark its presence by negating the value at the corresponding index. Then scan for the first positive index.

3. Walk through an example

Trace the algorithm on a small example (e.g., [3,4,-1,1]) to demonstrate correctness and handling of duplicates and out-of-range values.

4. Analyze complexity and trade-offs

State that the algorithm runs in O(n) time and O(1) extra space. Mention alternative approaches (e.g., sorting, hash set) and their trade-offs.

5. Discuss potential pitfalls and optimizations

Address issues like integer overflow when negating, handling duplicates, and ensuring the algorithm works when the array contains values larger than n. Suggest using a boolean array if modification is not allowed.

Key Points to Mention

Time complexity: O(n) with a constant number of passes.
Space complexity: O(1) extra space by modifying the input array.
Handling of negative numbers and zeros by ignoring them.
Using the array indices to represent presence of numbers (value x maps to index x-1).
Edge cases: empty array, all negatives, array containing 1..n.
Alternative approaches: sorting (O(n log n)) or hash set (O(n) space) and when to use them.

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