How do you solve Longest String Chain on LeetCode?

Longest String Chain (LeetCode #1048) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n * m) time complexity and O(n) space complexity. Key insight: The relationship between words can be visualized as a directed graph where edges represent valid predecessor relationships.

What is the brute force solution for Longest String Chain?

The brute force approach for Longest String Chain is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach checks every possible combination of words to see if they can form a chain. This method is straightforward but inefficient as it doesn't leverage any structure in the problem. The optimal Optimal Solution approach improves this to O(n * m).

What algorithm or data structure is used to solve Longest String Chain?

Longest String Chain uses the following concepts: Array, Hash Table, Two Pointers, String, Dynamic Programming, Sorting. The recommended patterns to study are: Hash Map, Dynamic Programming, Sorting.

What are the interview tips for Longest String Chain?

Always clarify the problem statement and constraints before jumping into coding. Think about edge cases, such as when the input array is empty or contains only one word. Explain your thought process and the reasoning behind each step as you code.

What are common mistakes when solving Longest String Chain?

Failing to consider all possible predecessor words when updating chain lengths. Not sorting the words before processing, which can lead to incorrect results.

#1048

Longest String Chain

Medium

ArrayHash TableTwo PointersStringDynamic ProgrammingSortingHash MapDynamic ProgrammingSorting

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

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Intuition

Time O(n * m)Space O(n)

The optimal solution uses dynamic programming to build the longest chain by processing words in order of their lengths. By checking if a word can be formed by removing a character from a longer word, we can efficiently calculate the longest chain.

⚙️

Algorithm

3 steps

1Step 1: Sort the words by their lengths.
2Step 2: Use a dictionary to store the maximum chain length for each word.
3Step 3: For each word, check all possible predecessors (words with one character removed) and update their chain lengths.

solution.py12 lines

1def longestStrChain(words):
2    words.sort(key=len)
3    dp = {}
4    max_length = 1
5    for word in words:
6        dp[word] = 1
7        for i in range(len(word)):
8            predecessor = word[:i] + word[i+1:]
9            if predecessor in dp:
10                dp[word] = max(dp[word], dp[predecessor] + 1)
11        max_length = max(max_length, dp[word])
12    return max_length

ℹ

Complexity note: The time complexity is O(n * m) where n is the number of words and m is the average length of the words, due to the sorting and the nested loop for checking predecessors. The space complexity is O(n) because we store the maximum chain lengths in a dictionary.

1The relationship between words can be visualized as a directed graph where edges represent valid predecessor relationships.
2Sorting words by length allows us to build chains incrementally, ensuring we only check valid predecessors.

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