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Amazon·Software Engineer·Online Assessment (OA)·Intermediate

Intermediate
Apr 2026

Summary

Amazon coding problem, bit manipulation heavy. The kind of question where you think you see the answer and then realize you're missing half the constraints.

Questions Asked (1)

Q1

You're given an integer array of length n along with two integers k and m. You can increment any elements by 1, using at most k total increments (an element can be incremented more than once). After applying your increments, pick m elements from the resulting array and compute their bitwise AND. Return the maximum possible value of that AND.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

Spent way too long thinking about this greedily before realizing you really need to think bit by bit from the top down.

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AI HintsAI Generated

Suggested Approach

Use a greedy bit-by-bit construction from the most significant bit to the least, checking at each step whether it's possible to make the current candidate answer achievable with the given increments. For each bit, determine if you can select m elements and increment them so that all have that bit set in the candidate answer, while respecting the total increment budget k. This reduces the problem to a feasibility check that can be solved by computing the minimum increments needed for each element to satisfy the bit requirements.

Pro tip: Clearly separate the feasibility check from the greedy bit construction, and explain how you compute the minimum increments for each element to meet the bitmask requirements. This shows structured thinking and avoids getting lost in implementation details.

1. Understand the problem and constraints

Restate the problem: you can increment elements up to k times total, then choose m elements to maximize their bitwise AND. Clarify that increments can be distributed arbitrarily and that the AND is computed after all increments.

2. Greedy bit-by-bit construction

Start with the most significant bit and decide if it can be set in the final answer. Maintain a candidate answer mask and test if it's feasible to achieve that mask with the given k increments.

3. Feasibility check for a candidate mask

For each element, compute the minimum increments needed so that the element has all bits of the candidate mask set (i.e., (element + increments) & mask == mask). Sort these costs and check if the sum of the m smallest costs is ≤ k.

4. Iterate and finalize

If feasible, keep the bit set in the answer; otherwise, leave it unset. Continue to the next lower bit until all bits are processed. Return the final answer.

5. Analyze complexity and edge cases

Discuss time complexity (O(n log n * number of bits) due to sorting per bit) and space complexity. Mention edge cases like k=0, m=1, or all elements already having high bits set.

Key Points to Mention

  • Greedy approach from most significant bit to least significant bit
  • Feasibility check: minimum increments to make an element satisfy a bitmask
  • Sorting the increment costs and picking the m smallest
  • Total increment budget constraint (sum ≤ k)
  • Bitwise AND properties and how setting bits affects the result
  • Time and space complexity analysis

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