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Can you reduce this problem to a classic problem?
The problem is equivalent to finding any palindromic subsequence of length at least N-K where N is the length of the string.
Try to find the longest palindromic subsequence.
Use DP to do that.
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Yes, variations of palindrome transformation problems frequently appear in FAANG and other top tech interviews. They test understanding of dynamic programming, string manipulation, and subsequence concepts.
The optimal approach uses dynamic programming to compute the longest palindromic subsequence (LPS). If the LPS length is at least n − k, the string can become a palindrome after at most k deletions. This method efficiently avoids trying every deletion combination.
A 2D dynamic programming table is typically used to store results for substrings or subsequences. It helps reuse previously computed values when comparing characters or computing the longest palindromic subsequence.
The longest palindromic subsequence tells us the maximum part of the string that already forms a palindrome. If the rest of the characters are within the allowed k deletions, the string can be converted into a palindrome.