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

Intermediate

Apr 2026

Summary

Amazon SWE online assessment with a greedy/backtracking sequence construction problem. Pretty niche problem type, not your typical LC medium.

Questions Asked (1)

Given an integer array of values and a binary string representing which indices are currently available, build a sequence of length m by repeatedly picking an available index and appending its value. After each pick, any index immediately to the right of an available index gets unlocked. Return the lexicographically largest sequence possible.

Algorithms & Data Structures

Author's notes

This one took me a while to even parse the problem statement.

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AI HintsAI Generated

Suggested Approach

Model the problem as a greedy selection with a priority queue: at each step, choose the available index with the largest value, then unlock the next index if it exists. Use a max-heap keyed by value (and index for tie-breaking) to efficiently pick the best candidate. Continue until m elements are selected.

Pro tip: Clarify the unlocking rule: only the immediate right neighbor of the picked index becomes available, not all right neighbors. Also, if multiple indices have the same value, picking the leftmost one may unlock more options, but since the sequence is built by value, tie-breaking doesn't affect lexicographic order—still, mention it to show thoroughness.

1. Understand the problem and constraints

Restate the problem: given an array and a binary string of available indices, repeatedly pick an available index, append its value, and unlock the index immediately to its right. Goal: lexicographically largest sequence of length m.

2. Identify the greedy choice

At each step, to maximize the lexicographic order, we should pick the available index with the largest value. If there are ties, any choice yields the same value, but consider which unlocks more future options.

3. Design an efficient data structure

Use a max-heap (priority queue) to store available indices, ordered by value descending. When an index is picked, if the next index exists and is not yet available, unlock it and push it into the heap.

4. Simulate the process

Initialize the heap with all initially available indices. Repeat m times: pop the max-value index, append its value to the result, and unlock the next index if applicable. Return the result.

5. Analyze complexity and edge cases

Time: O((n + m) log n) due to heap operations. Space: O(n). Handle edge cases: m > number of available indices? (Problem guarantees m is valid), all values equal, unlocking beyond array bounds.

Key Points to Mention

Greedy strategy: always pick the maximum available value to ensure lexicographically largest sequence.
Use a max-heap (priority queue) to efficiently retrieve the maximum available value.
Unlocking mechanism: only the immediate right neighbor becomes available after picking an index.
Tie-breaking: when values are equal, the choice doesn't affect the sequence's lexicographic order, but may affect future availability.
Time complexity: O((n + m) log n) with heap operations; space complexity O(n).
Edge cases: ensure indices are within bounds when unlocking, and handle cases where no available indices exist (though problem guarantees m is valid).

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