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

IntermediatePending

Jun 2026Remote

Summary

Took the Amazon SDE online assessment recently, two questions total. Passed all the debugging test cases but only got 12 out of 15 on the DSA problem, so now I'm just sitting here wondering if that's enough to move forward.

Questions Asked (2)

Solve a DSA coding problem under timed OA conditions.

Algorithms & Data Structures

Author's notes

Got 12/15 test cases which felt okay in the moment but now I keep second-guessing it.

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AI HintsAI Generated

Suggested Approach

First, clarify the problem constraints and edge cases, then identify the optimal data structure and algorithm by analyzing time/space complexity. Implement a clean solution, test with examples, and optimize if needed.

Pro tip: In timed OAs, prioritize passing all test cases over premature optimization; start with a brute-force solution if stuck, then refine. Always consider Amazon's leadership principles like Customer Obsession by ensuring your code handles edge cases robustly.

1. Understand the Problem

Read the problem statement carefully, identify input/output formats, constraints, and edge cases. Ask clarifying questions if allowed.

2. Plan the Approach

Choose the right data structures and algorithm based on constraints. Outline steps and analyze time/space complexity.

3. Implement the Solution

Write clean, modular code with meaningful variable names. Handle edge cases and use helper functions if needed.

4. Test and Debug

Run through provided examples and additional edge cases. Use print statements or a debugger to fix errors.

5. Optimize if Time Permits

Review for potential optimizations, but only if all test cases pass and time remains. Avoid over-engineering.

Key Points to Mention

Time and space complexity analysis of the chosen algorithm
Edge cases such as empty input, large inputs, and duplicates
Choice of data structures (e.g., hash maps, heaps, trees) and why
Trade-offs between different approaches (e.g., brute force vs. optimized)
Code readability and maintainability
Testing strategy including unit tests and boundary conditions

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

Debug a piece of existing code to identify and fix errors.

Algorithms & Data StructuresRoot Cause Analysis

Author's notes

Full marks on this one, 6/6.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the expected behavior and reproducing the bug with a minimal test case. Then systematically trace the code to isolate the root cause, fix it, and verify the fix with tests and edge cases.

Pro tip: Verbally walk through your debugging process as if pair programming—Amazon values candidates who communicate their reasoning clearly and involve the interviewer in the problem-solving journey.

1. Understand and Reproduce

Ask clarifying questions about the code's purpose and expected behavior. Reproduce the bug with a specific input to confirm the issue.

2. Isolate the Fault

Use systematic debugging techniques like binary search, print statements, or a debugger to narrow down the faulty section. Form hypotheses and test them.

3. Identify Root Cause

Analyze the isolated code to determine why the bug occurs, considering edge cases, off-by-one errors, null handling, or algorithmic flaws.

4. Implement and Verify Fix

Apply a minimal, correct fix and test it against the original failing case plus additional edge cases to ensure no regressions.

5. Reflect and Prevent

Discuss how to prevent similar bugs, such as adding unit tests, improving code clarity, or using static analysis tools.

Key Points to Mention

Reproducing the bug with a minimal test case to confirm the issue
Using binary search or divide-and-conquer to isolate the faulty code
Checking edge cases like empty inputs, null values, and boundary conditions
Considering time and space complexity when fixing algorithmic issues
Writing unit tests to verify the fix and prevent regressions
Communicating your thought process clearly and involving the interviewer

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