What is the time complexity of Find the Lexicographically Largest String From the Box I?

The optimal solution for Find the Lexicographically Largest String From the Box I runs in O(n) time and uses O(n) space. We only check substrings of limited length, leading to linear time complexity.

What is the brute force solution for Find the Lexicographically Largest String From the Box I?

The brute force approach for Find the Lexicographically Largest String From the Box I is Brute Force, with O(n²) time complexity and O(1) space complexity. Generate all possible splits of the string and keep track of the largest substring found. This method is straightforward but inefficient due to the number of combinations. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Find the Lexicographically Largest String From the Box I?

Find the Lexicographically Largest String From the Box I uses the following concepts: Two Pointers, String, Enumeration. The recommended patterns to study are: Substring Search, Greedy Algorithms.

What are the interview tips for Find the Lexicographically Largest String From the Box I?

Clarify constraints and edge cases. Discuss brute force before jumping to optimization. Practice substring problems for familiarity.

What are common mistakes when solving Find the Lexicographically Largest String From the Box I?

Generating all splits instead of focusing on substring lengths. Not considering edge cases like repeated characters.

#3403

Find the Lexicographically Largest String From the Box I

Medium

Two PointersStringEnumerationSubstring SearchGreedy Algorithms

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

💡

Intuition

Time O(n)Space O(n)

Instead of generating all splits, we can find the largest substring of length up to n - numFriends + 1 starting from each index. This reduces unnecessary computations.

⚙️

Algorithm

3 steps

1Step 1: Initialize maxStr as an empty string.
2Step 2: Loop through the string and check substrings of length up to n - numFriends + 1.
3Step 3: Update maxStr if a larger substring is found.

solution.py7 lines

1def largestSubstring(word, numFriends):
2    max_str = ""
3    n = len(word)
4    for i in range(n):
5        for j in range(i + 1, min(n, i + n - numFriends + 1)):
6            max_str = max(max_str, word[i:j])
7    return max_str

ℹ

Complexity note: We only check substrings of limited length, leading to linear time complexity.

1Focus on substring lengths based on numFriends.
2Lexicographical comparison can be efficiently managed.

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