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Walmart Labs·Mobile Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Walmart Labs mobile engineer interview that leaned surprisingly algorithmic. The main challenge was an array permutation problem that pushed you to think beyond brute force, which felt a bit out of left field for a mobile role.

Questions Asked (1)

Q1

Given two equal-length arrays A and B, define s as the sum of B[i] where B[i] is strictly greater than A[i]. Find the maximum possible value of s across all permutations of B.

Algorithms & Data Structures
Author's notes

This one took me a minute to even understand what they were asking.

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AI HintsAI Generated

Suggested Approach

Sort both arrays and use a greedy two-pointer strategy: for each element in sorted A, find the smallest element in sorted B that is strictly greater, sum it, and remove it. This maximizes the sum by ensuring each winning B is as small as possible, preserving larger elements for harder-to-beat A's.

Pro tip: After solving, discuss how the greedy choice is optimal via an exchange argument, and mention that the problem is equivalent to maximizing the sum of a maximum matching in a bipartite graph where edges exist if B[i] > A[i].

1. Understand the problem

Restate the goal: permute B to maximize the sum of B[i] where B[i] > A[i]. Clarify that only strictly greater elements contribute, and each B element can be used at most once.

2. Sort both arrays

Sort A and B in ascending order. This simplifies the process of finding the smallest B that beats each A.

3. Apply two-pointer greedy

Use two pointers: iterate through sorted A, and for each A[i], advance a pointer in B until finding the smallest B[j] > A[i]. If found, add B[j] to sum and mark it used; otherwise, skip A[i].

4. Prove optimality

Explain that the greedy choice is safe: using the smallest possible B for each A leaves larger B's available for other A's, which can only increase or maintain the sum.

5. Analyze complexity

Sorting takes O(n log n), and the two-pointer pass takes O(n), so overall O(n log n) time and O(1) extra space (if sorting in place).

Key Points to Mention

  • Greedy algorithm with sorting and two pointers
  • Strict inequality condition (B[i] > A[i])
  • Optimality proof via exchange argument
  • Time complexity: O(n log n) due to sorting
  • Space complexity: O(1) extra space if sorting in place
  • Edge cases: no valid pairs, all pairs valid, duplicates in arrays

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