Passed all 15 test cases, nothing too wild.
Start by clarifying the problem constraints and edge cases, then discuss a brute-force solution before optimizing with appropriate data structures or algorithms. Focus on explaining your thought process clearly, analyzing time and space complexity, and testing with examples.
Pro tip: Amazon values customer obsession and ownership; relate your solution to scalability and real-world impact, and always consider edge cases like empty inputs or large data.
Ask clarifying questions to confirm input/output formats, constraints, and edge cases. Restate the problem in your own words to ensure alignment.
Discuss a brute-force solution first, then identify bottlenecks and propose optimizations using suitable data structures or algorithms.
Write clean, modular code with meaningful variable names. Walk through a few test cases, including edge cases, to verify correctness.
Clearly state the time and space complexity of your solution and compare it to alternatives, explaining trade-offs.
If time permits, discuss potential improvements or variations, and how your solution might scale for larger inputs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Got 5 out of 6 test cases passing and then panicked on the last one.
Start by running the test cases to see which fail and read the error messages carefully. Then trace the code execution for each failing test, using print statements or a debugger to isolate the faulty logic. Fix one bug at a time and re-run tests to ensure no regressions.
Pro tip: Before fixing anything, write down your hypothesis about the root cause and verify it with a minimal test case. This prevents you from making random changes that might break other parts of the code.
Read the problem statement, the code, and the test cases to understand expected behavior and identify what might be wrong.
Execute the test suite to see which tests fail and examine the error messages and stack traces to pinpoint the issue.
Use debugging techniques like print statements, breakpoints, or code inspection to trace the execution and find the root cause.
Implement the fix, then re-run the tests to confirm the failure is resolved and no new issues are introduced.
Check for edge cases, code quality, and potential improvements, ensuring the solution is robust and efficient.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.