I went straight to the hashmap trick from the classic consecutive sequence problem and then realized mid-explanation it doesn't cleanly port over.
Clarify the problem constraints and edge cases, then propose an efficient algorithm such as sorting the distinct values and using dynamic programming or two pointers to find the longest chain. Discuss time and space complexity, and consider trade-offs between different approaches.
Pro tip: Demonstrate Amazon leadership principles by proactively discussing scalability and edge cases, and by explaining how you would test and optimize the solution for large inputs.
Ask questions to confirm the definition of 'chain', whether the array can contain duplicates, and the expected input size. This ensures you understand the problem correctly and can tailor your solution.
Briefly describe a naive solution (e.g., checking all permutations) to establish a baseline, then explain why it's inefficient and motivate the need for optimization.
Explain that after sorting the distinct values, the problem reduces to finding the longest subsequence where adjacent differences are ≤ k. Use dynamic programming or two pointers to achieve O(n log n) time.
State the time and space complexity of your solution and compare it with alternatives (e.g., using a balanced BST). Discuss scenarios where one approach might be preferred.
Mention edge cases like empty array, k=0, or all elements equal, and describe how you would test the solution for correctness and performance.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.