Amazon·Software Engineer·Onsite - Coding / Algorithms·Intermediate

IntermediatePrefer not to say

Jun 2026

Summary

Amazon SWE coding round, focused on an in-place array merge problem. The interviewer wanted more than just code, they pushed hard on trade-offs between different sorting and merging strategies, which I wasn't fully prepared for.

Questions Asked (1)

You have two unsorted arrays where the first has enough extra capacity to hold both. Merge them into a single sorted array in place, without allocating a new array. Walk through the different approaches and their trade-offs.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I jumped straight to 'just sort the whole thing after appending' and the interviewer kind of nodded slowly in that way that tells you they're waiting for more.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints, such as whether the first array has a known number of valid elements and extra capacity. Then, discuss the optimal approach of merging from the end to avoid overwriting, and compare it with alternatives like concatenation followed by sorting or using a temporary array. Emphasize time and space complexity trade-offs and why the in-place backward merge is preferred.

Pro tip: Mention that merging from the end is a common pattern in problems like 'Merge Sorted Array' on LeetCode, and it's crucial to handle edge cases like one array being empty. Also, note that if the arrays are unsorted, you might need to sort them first, but the problem likely assumes they are sorted; clarify this assumption.

1. Clarify assumptions and constraints

Ask if the arrays are sorted or unsorted, if the first array's extra capacity is exactly the size of the second, and if there are duplicate elements. Confirm that 'in place' means no additional array allocation.

2. Discuss naive approaches

Mention concatenating the second array to the first and then sorting, which takes O((m+n) log(m+n)) time and O(1) extra space if using in-place sort, but may not be optimal. Also, consider using a temporary array to merge and then copy back, which uses O(m+n) extra space.

3. Present optimal approach: merge from the end

If the arrays are sorted, use three pointers: one for the end of the first array's valid elements, one for the end of the second array, and one for the end of the merged array. Compare elements from the back and place the larger one at the end, moving pointers backward. This avoids overwriting and achieves O(m+n) time and O(1) extra space.

4. Analyze trade-offs and edge cases

Compare time and space complexities of each approach. Discuss edge cases: one array empty, all elements of one array smaller, duplicates, and integer overflow if using sentinel values. Explain why backward merge is optimal for sorted arrays.

5. Conclude with recommendation

Summarize that for sorted arrays, the backward merge is the best approach. If arrays are unsorted, sorting first may be necessary, but clarify that the problem likely assumes sorted arrays. Emphasize clarity in communication and handling edge cases.

Key Points to Mention

Time complexity: O(m+n) for backward merge vs O((m+n) log(m+n)) for concatenate and sort.
Space complexity: O(1) extra space for backward merge, O(m+n) for temporary array approach.
In-place merging requires careful pointer manipulation to avoid overwriting unprocessed elements.
Edge cases: empty arrays, duplicates, and arrays of different sizes.
Assumption clarification: whether arrays are sorted or unsorted, and if extra capacity is exactly the size needed.
Alternative approaches: using a temporary array, concatenating and sorting, or using a heap for unsorted arrays.

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