Find the Lexicographically Largest String From the Box I - Problem
Alice is organizing an exciting word-splitting game for her friends! 🎮
Given a string word and an integer numFriends, Alice runs multiple rounds where each round:
- The
wordis split into exactlynumFriendsnon-empty substrings - Each split must be unique - no two rounds can have the same split pattern
- All resulting substrings are collected in a box
Your task is to find the lexicographically largest string that will be in the box after all possible unique splits are completed.
Example: If word = "abc" and numFriends = 2:
- Split 1: ["a", "bc"] → box contains: "a", "bc"
- Split 2: ["ab", "c"] → box contains: "a", "bc", "ab", "c"
- Lexicographically largest: "c"
Input & Output
example_1.py — Basic Split
$
Input:
word = "abc", numFriends = 2
›
Output:
"c"
💡 Note:
Possible splits: ["a", "bc"], ["ab", "c"]. All substrings: "a", "ab", "bc", "c". Lexicographically largest is "c".
example_2.py — Single Friend
$
Input:
word = "leetcode", numFriends = 1
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Output:
"leetcode"
💡 Note:
Only one split possible: ["leetcode"]. The entire word is the only and largest substring.
example_3.py — Multiple Max Characters
$
Input:
word = "aaaa", numFriends = 3
›
Output:
"aa"
💡 Note:
Possible splits include ["a", "a", "aa"], ["a", "aa", "a"], ["aa", "a", "a"]. The largest substring is "aa".
Visualization
Tap to expand
Understanding the Visualization
1
Identify Premium Spots
Look for the largest character in the pizza - these are potential starting points for premium pieces
2
Test Cut Patterns
For each premium spot, try different piece sizes and check if valid cutting patterns exist
3
Validate Cuts
Ensure that after taking a piece, the remaining pizza can still be cut into the required number of pieces
4
Select Best Piece
Among all valid pieces, choose the lexicographically largest one
Key Takeaway
🎯 Key Insight: Instead of generating all possible cuts (expensive), focus on positions with the largest character and verify if valid cutting patterns exist. This reduces complexity from exponential to polynomial time.
Time & Space Complexity
Time Complexity
O(C(n-1, k-1) * n)
C(n-1, k-1) ways to choose split positions, each requiring O(n) time to generate substrings
✓ Linear Growth
Space Complexity
O(n * C(n-1, k-1))
Storing all possible substrings from all splits
⚡ Linearithmic Space
Constraints
- 1 ≤ numFriends ≤ word.length ≤ 1000
- word consists of lowercase English letters
- Each split must produce exactly numFriends non-empty substrings
💡
Explanation
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