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As with any good dp problem that uses palindromes, try building the palindrome from the edges
The prime point is to check that no two adjacent characters are equal, so save the past character while building the palindrome.
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Variations of longest palindromic subsequence and advanced dynamic programming problems are common in FAANG interviews. Problems like this test understanding of state design, constraints, and substring DP techniques.
The optimal approach uses dynamic programming on substrings combined with character tracking. A 3D DP state stores the longest valid palindrome for a substring with a specific outer character, ensuring adjacent characters are different.
A multidimensional dynamic programming array is the most suitable structure. It allows efficient storage of substring results and character constraints while building the solution from smaller substrings.
Unlike the classic LPS problem, this version restricts consecutive characters from being the same. Tracking the outer character in the DP state helps enforce this constraint when extending smaller palindromes.