← Walmart Labs Interview Insights
I jumped straight to the hashmap approach and coded it up fast, but then they asked about the tie-breaking rules and I realized my solution just returned the first pair it found, which isn't guaranteed to have the smallest i.
Use a hash map to store each element's value and index as you iterate through the array. For each element, check if its complement (target - current) exists in the map; if so, you have a valid pair. To handle tie-breaking, ensure you consider all pairs and select the one with the smallest first index, then smallest second index.
Pro tip: Clarify with the interviewer whether the array can contain duplicates and whether the same element can be used twice. Also, discuss the trade-off between time and space complexity, and mention that if the array were sorted, a two-pointer approach could be more space-efficient.
Ask about input constraints: array size, possible values, duplicates, and whether the same element can be used twice. Confirm the tie-breaking rule and expected return format.
Decide between a hash map (for O(n) time) and sorting with two pointers (for O(n log n) time, O(1) space). Explain why hash map is suitable for unsorted arrays.
Iterate through the array, storing each element's value and index in a hash map. For each element, check if its complement exists; if so, record the pair. After finding all pairs, select the one with the smallest first index, then smallest second index.
State that the hash map approach runs in O(n) time and O(n) space on average. Mention that sorting would allow O(1) space but O(n log n) time, and that tie-breaking might require extra handling.
Walk through a few examples, including duplicates, negative numbers, and cases with multiple valid pairs, to verify the tie-breaking logic and correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the problem constraints (e.g., array size, value range) and then propose a two-pointer approach after sorting to achieve O(n^2) time complexity. Explain how sorting enables efficient duplicate skipping and why this is optimal compared to brute force.
Pro tip: Mention that sorting modifies the input, so if the original order must be preserved, you'd need to copy the array first—showing awareness of side effects. Also, emphasize that the two-pointer approach is preferred over hash set for better space efficiency and easier duplicate handling.
Ask about input size, value ranges, and whether the array can be modified. Confirm that duplicate triplets should be ignored and that the output should contain unique triplets.
Briefly mention the O(n^3) brute force approach to establish a baseline, then explain why it's inefficient for large inputs.
Sort the array, then iterate through each element as the first number of the triplet. Use two pointers (left and right) to find pairs that sum to the negative of the current element.
Explain how to skip duplicate elements for the first number and for the two pointers to ensure unique triplets. Mention that sorting groups duplicates together, making skipping straightforward.
State that time complexity is O(n^2) due to sorting O(n log n) and the nested loop, and space complexity is O(1) or O(n) depending on sorting implementation. Compare with hash-based approach.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.