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Amazon·Software Engineer·Onsite - Coding / Algorithms·Intermediate

IntermediatePrefer not to say
May 2026

Summary

Amazon SWE coding round with a string manipulation problem that's trickier than it looks. The hint pointing to LC 664 is actually useful if you've seen it before, but I hadn't.

Questions Asked (1)

Q1

Given a string, find the minimum number of deletion operations to make it empty, where each operation deletes a consecutive group of identical characters.

Algorithms & Data Structures
Author's notes

Took me a while to even parse what the operation was doing.

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AI HintsAI Generated

Suggested Approach

First, clarify that the problem is equivalent to finding the minimum number of moves to remove all characters, where each move removes a contiguous block of identical characters. Then, propose a dynamic programming solution that considers the optimal strategy of either removing a block entirely or merging it with a matching character later to reduce total moves.

Pro tip: Demonstrate awareness of the problem's similarity to 'Strange Printer' and 'Remove Boxes', and mention that while a greedy approach might seem intuitive, it fails for cases like 'aba' where merging non-adjacent identical characters is beneficial.

1. Understand the problem

Restate the problem in your own words and confirm with the interviewer that each operation removes a contiguous group of identical characters, and the goal is to minimize the number of such operations.

2. Identify the optimal substructure

Recognize that the problem exhibits optimal substructure: the minimum deletions for a substring can be computed from smaller substrings. This suggests a dynamic programming approach.

3. Define the DP state and recurrence

Define dp[i][j] as the minimum deletions to remove substring s[i..j]. The base case is dp[i][i] = 1. For the recurrence, consider removing s[i] separately (1 + dp[i+1][j]) or merging it with a matching character s[k] (i < k <= j) to reduce operations: dp[i][j] = min(dp[i][j], dp[i+1][k-1] + dp[k][j]).

4. Optimize and analyze complexity

The DP has O(n^2) states and O(n) transition per state, leading to O(n^3) time and O(n^2) space. Mention that this is acceptable for typical constraints (n <= 100) and discuss potential optimizations if needed.

5. Test with examples

Walk through a few examples like 'aba' (answer 2) and 'abc' (answer 3) to validate the recurrence and ensure the logic handles merging correctly.

Key Points to Mention

  • Dynamic programming approach with state dp[i][j] representing the minimum deletions for substring s[i..j].
  • Recurrence relation: dp[i][j] = min(1 + dp[i+1][j], min_{k: s[k]==s[i]} (dp[i+1][k-1] + dp[k][j])).
  • Base case: dp[i][i] = 1 for all i.
  • Time complexity O(n^3) and space complexity O(n^2), with possible optimization to O(n^2) using memoization and pruning.
  • Comparison to similar problems like 'Strange Printer' and 'Remove Boxes' to show pattern recognition.
  • Edge cases: empty string (0 deletions), single character (1 deletion), all identical characters (1 deletion).

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