My first instinct was correct: for each block, just count mismatched mirror pairs and each mismatch costs one replacement.
First, clarify the problem and edge cases, then propose an efficient solution that groups characters by their position within each block and counts the minimum replacements per group. Analyze time and space complexity, and discuss potential trade-offs or optimizations.
Pro tip: Emphasize that the minimum replacements for each group is the group size minus the maximum frequency of any character in that group, and mention that this approach generalizes to any k. This shows you understand the core insight and can communicate it clearly.
Restate the problem in your own words, confirm that the string length is divisible by k, and ask about edge cases (e.g., k=1, k=length).
Explain that characters at the same offset within each block must be equal to form palindromes, so we can process each offset independently.
For each offset from 0 to k-1, collect all characters at that offset across blocks, count their frequencies, and compute the minimum replacements as the group size minus the maximum frequency.
State that the time complexity is O(n) where n is the string length, and space complexity is O(n) or O(1) depending on implementation (e.g., using a fixed-size array for frequencies).
Mention that the solution is optimal and can be implemented in a single pass; discuss potential variations like handling multiple test cases or streaming input.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.