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

IntermediatePrefer not to say
May 2026

Summary

Got an Intuit coding problem that looked deceptively clean on the surface but had some real depth once you started thinking about all substrings. The DNA palindrome thing is one of those problems where the brute force is obvious but the expected solution is not.

Questions Asked (1)

Q1

Given a string of DNA characters, for every possible substring, find the minimum number of character swaps needed to make that substring a palindrome. Return the total sum of these minimums across all substrings.

Algorithms & Data Structures
Author's notes

I spent way too long on the brute force before realizing the substring count alone would wreck my runtime.

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AI HintsAI Generated

Suggested Approach

First, clarify the problem: for each substring, the minimum swaps to make it a palindrome equals the number of mismatched character pairs divided by 2. Then, design an efficient algorithm, likely using dynamic programming or prefix sums, to compute this sum over all substrings without enumerating all O(n^2) substrings naively.

Pro tip: Mention that the minimum swaps for a substring is exactly half the number of mismatched pairs, and that you can compute the total sum in O(n^2) time by expanding around centers or using DP, which is optimal for this problem.

1. Clarify the problem

Restate the problem to ensure understanding: for each substring, find the minimum adjacent swaps to make it a palindrome, then sum these minimums. Confirm that swaps are adjacent and that we only consider substrings of length >= 2.

2. Derive the formula

Show that for a substring, the minimum number of swaps equals the number of mismatched character pairs divided by 2. Explain that each swap can fix at most one mismatched pair.

3. Design an efficient algorithm

Propose an O(n^2) solution: iterate over all possible centers (for odd and even length palindromes) and expand outward, maintaining the count of mismatches. Alternatively, use DP to compute the sum of mismatches for all substrings.

4. Analyze complexity

State that the time complexity is O(n^2) and space complexity is O(1) or O(n) depending on implementation. Justify why this is optimal given the need to consider all substrings.

5. Test with examples

Walk through a small example, such as 'abba' or 'abc', to verify the formula and algorithm. Discuss edge cases like empty string, single character, and strings with all same characters.

Key Points to Mention

  • Minimum swaps for a substring equals half the number of mismatched pairs.
  • Use center expansion to efficiently compute mismatches for all substrings.
  • Time complexity O(n^2) is optimal for this problem.
  • Handle both odd and even length palindromes.
  • Edge cases: empty string, single character, all same characters.
  • Potential optimization: use prefix sums to avoid recomputing mismatches.

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