Given a string s, you can transform every letter individually to be lowercase or uppercase to create another string.
Return a list of all possible strings we could create. Return the output in any order.
Example 1:
Input: s = "a1b2" Output: ["a1b2","a1B2","A1b2","A1B2"]
Example 2:
Input: s = "3z4" Output: ["3z4","3Z4"]
Constraints:
1 <= s.length <= 12s consists of lowercase English letters, uppercase English letters, and digits.In this approach, we use a backtracking algorithm to generate all possible letter case permutations for each character in the string. We iterate over each character and decide to either transform it (if it's a letter) or leave it unchanged. By following this approach, we can explore all possible combinations.
The C solution employs a recursive backtracking method to explore each character's transformation possibilities. It toggles the case of letters using the XOR operation and makes recursive calls to explore each possibility. The program handles string duplication and manages a list of results dynamically.
C++
Java
Python
C#
JavaScript
Time Complexity: O(2^n), where n is the number of letters in the string.
Space Complexity: O(2^n) for storing the results.
This approach utilizes bit manipulation to generate permutations. Each letter can be either in uppercase or lowercase, and we represent each possibility with bits. By iterating through all possible binary combinations (where a bit signifies changing the case of a letter), we construct the result directly.
The Python solution calculates all possible transformations using bit manipulation for the powerset of letters. It iteratively transforms characters based on the current state of bit masking and then constructs each permutation by appending to the result list.
JavaScript
Time Complexity: O(2^n), where n is the number of letters since we iterate over each possible set of transformations.
Space Complexity: O(2^n) for storage of permutations.
| Approach | Complexity |
|---|---|
| Backtracking Approach | Time Complexity: O(2^n), where n is the number of letters in the string. |
| Iterative Bit Manipulation | Time Complexity: O(2^n), where n is the number of letters since we iterate over each possible set of transformations. |
Letter Case Permutation | Recursion • Aditya Verma • 74,078 views views
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