How do you solve Longest Chunked Palindrome Decomposition on LeetCode?

Longest Chunked Palindrome Decomposition (LeetCode #1147) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n²) time complexity and O(n) space complexity. Key insight: Understanding the palindrome structure is crucial for splitting the string correctly.

What is the brute force solution for Longest Chunked Palindrome Decomposition?

The brute force approach for Longest Chunked Palindrome Decomposition is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves checking all possible ways to split the string into substrings and verifying if they form a palindrome structure. This method is straightforward but inefficient as it explores all combinations. The optimal Optimal Solution approach improves this to O(n²).

What are the interview tips for Longest Chunked Palindrome Decomposition?

Always clarify the problem requirements and constraints before diving into coding. Think about edge cases, such as very short strings or strings that are already palindromes. Explain your thought process clearly while coding, as this shows your understanding of the problem.

What are common mistakes when solving Longest Chunked Palindrome Decomposition?

Failing to consider all possible splits in the brute force approach. Not properly initializing or updating the DP array in the optimal solution.

#1147

Longest Chunked Palindrome Decomposition

Hard

Two PointersStringDynamic ProgrammingGreedyRolling HashHash FunctionDynamic ProgrammingTwo Pointers

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n²)
Space	O(1)	O(n)

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Intuition

Time O(n²)Space O(n)

The optimal solution uses a dynamic programming approach to efficiently find the longest chunked palindrome decomposition. By leveraging previously computed results, we can avoid redundant checks and improve performance.

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Algorithm

3 steps

1Step 1: Initialize a DP array where dp[i] represents the maximum k for the substring text[0:i].
2Step 2: Iterate through the string and for each position, check for possible palindromic chunks.
3Step 3: Update the DP array based on valid splits found.

solution.py11 lines

1def longestChunkedPalindromeDecomposition(text):
2    n = len(text)
3    dp = [0] * (n + 1)
4    dp[0] = 1
5    for i in range(1, n + 1):
6        for j in range(i):
7            left = text[j:i]
8            right = text[n - (i - j):n - j]
9            if left == right:
10                dp[i] = max(dp[i], dp[j] + 1)
11    return dp[n]

ℹ

Complexity note: The time complexity remains O(n²) due to the nested loops, but we use a DP array to store results, which improves efficiency by avoiding redundant calculations.

1Understanding the palindrome structure is crucial for splitting the string correctly.
2Dynamic programming can significantly reduce redundant checks by storing intermediate results.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.