Passed all test cases so I don't think this was the issue.
Clarify the problem, constraints, and edge cases before diving into a solution. Discuss a brute-force approach first, then optimize using appropriate data structures and algorithms, analyzing time and space complexity. Write clean, modular code and test with examples, including edge cases.
Pro tip: Amazon values customer obsession and ownership; demonstrate these by proactively discussing how your solution scales, handles failures, and impacts the end user. Also, think aloud to showcase your problem-solving process.
Ask clarifying questions to ensure you fully understand the problem, including input/output formats, constraints, and edge cases. Restate the problem in your own words to confirm.
Start with a brute-force solution, then identify bottlenecks and propose optimizations using suitable data structures or algorithms. Discuss trade-offs between different approaches.
Outline the steps of your chosen algorithm, including pseudocode or high-level logic. Consider modularity and code organization.
Write clean, efficient code, explaining your reasoning as you go. Test with provided examples and additional edge cases, debugging as needed.
Analyze time and space complexity, and discuss potential improvements or alternative solutions. Consider scalability and real-world implications.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by understanding the code's purpose and expected behavior, then systematically trace the execution to identify where it deviates. Prioritize bugs by impact, fix them one at a time, and verify each fix with tests to ensure no regressions.
Pro tip: Demonstrate a methodical approach by explaining your thought process aloud, as Amazon values candidates who can articulate their debugging strategy and trade-offs. Also, consider edge cases and potential side effects of your fixes.
Read the code and any accompanying documentation to grasp its intended functionality and constraints. Clarify any ambiguities before diving into debugging.
Run the code with provided test cases or create minimal reproductions to observe the buggy behavior. This confirms the problem and provides a baseline for fixes.
Use debugging tools, logging, and code inspection to locate the root causes. Rank bugs by severity and impact on functionality to address critical issues first.
Apply targeted fixes, ensuring they address the root cause without introducing new issues. Write or run tests to validate each fix and check for regressions.
Summarize the bugs found, fixes applied, and any trade-offs made. Discuss how you would prevent similar issues in the future, such as adding tests or improving code reviews.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This is probably where things fell apart and I just didn't realize it.
Use the STAR method to structure your response, focusing on a specific situation where you navigated ambiguity or conflict as a software engineer. Emphasize how you applied Amazon's Leadership Principles, such as Customer Obsession and Ownership, to make decisions and drive results. Highlight your thought process, the actions you took, and the measurable impact of your decisions.
Pro tip: Demonstrate bias for action and customer obsession by explaining how you prioritized customer needs and took calculated risks in ambiguous situations. Show that you can disagree and commit while maintaining a focus on delivering results.
Briefly describe the situation, including the ambiguity or conflict, and your role. Highlight why it was challenging and what was at stake.
Detail the steps you took to analyze the situation, gather information, and consider different perspectives. Mention how you applied relevant Leadership Principles.
Explain the specific actions you took to resolve the ambiguity or conflict, including any trade-offs or decisions made. Emphasize collaboration and communication.
Share the results of your actions, including measurable impact on the project, team, or customer. If applicable, mention what you learned and how you applied it later.
Summarize how this experience demonstrates your ability to thrive in ambiguity and resolve conflicts, and connect it to the role and Amazon's culture.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.