You are given a string s
.
You can perform the following process on s
any number of times:
- Choose an index
i
in the string such that there is at least one character to the left of indexi
that is equal tos[i]
, and at least one character to the right that is also equal tos[i]
. - Delete the closest character to the left of index
i
that is equal tos[i]
. - Delete the closest character to the right of index
i
that is equal tos[i]
.
Return the minimum length of the final string s
that you can achieve.
Example 1:
Input: s = “abaacbcbb”
Output: 5
Explanation:
We do the following operations:
- Choose index 2, then remove the characters at indices 0 and 3. The resulting string is
s = "bacbcbb"
. - Choose index 3, then remove the characters at indices 0 and 5. The resulting string is
s = "acbcb"
.
Example 2:
Input: s = “aa”
Output: 2
Explanation:
We cannot perform any operations, so we return the length of the original string.
Constraints:
1 <= s.length <= 2 * 105
s
consists only of lowercase English letters.
Approach 01:
-
C++
-
Python
class Solution { public: int minimumLength(string str) { unordered_map<char, int> charFrequency; int length = str.length(); // Count the frequency of each character in the string for (char &ch : str) { ++charFrequency[ch]; } // Adjust the length based on character frequencies for (auto [character, frequency] : charFrequency) { if (frequency % 2 == 0 && frequency > 2) { length = length - frequency + 2; } else if (frequency % 2 != 0 && frequency > 2) { length = length - frequency + 1; } } return length; } };
class Solution: def minimumLength(self, s: str) -> int: charFrequency = {} length = len(s) # Count the frequency of each character in the string for ch in s: charFrequency[ch] = charFrequency.get(ch, 0) + 1 # Adjust the length based on character frequencies for character, frequency in charFrequency.items(): if frequency % 2 == 0 and frequency > 2: length = length - frequency + 2 elif frequency % 2 != 0 and frequency > 2: length = length - frequency + 1 return length
Time Complexity:
- Character Frequency Count:
We iterate through the string once to calculate the frequency of each character, which takes \( O(n) \), where \( n \) is the length of the string.
- Adjusting Length:
We iterate through the unordered map containing character frequencies. In the worst case, there are at most 26 entries (for lowercase English letters), making this step \( O(1) \).
- Overall Time Complexity:
\( O(n) \).
Space Complexity:
- Unordered Map:
The unordered map can store at most 26 entries for lowercase English letters, resulting in \( O(1) \) space usage.
- Additional Variables:
We use a constant amount of space for variables like
length
and loop iterators. - Overall Space Complexity:
\( O(1) \).