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This approach utilizes a two-pointer technique to simultaneously check from the left and from the right, aiming to fulfill the requirement of obtaining at least 'k' of each character ('a', 'b', 'c'). The key idea is to keep track of character counts from both ends and to update pointers strategically to achieve the minimum number of moves.
Time Complexity: O(n), where n is the length of the string, as every character is processed at most twice.
Space Complexity: O(1), as the storage requirement does not scale with input size beyond a fixed size.
1def takeCharacters(s: str, k: int) -> int:
2 from collections import Counter
3
4 n = len(s)
5 count = Counter(s)
6 if count['a'] < k or count['b'] < k or count['c'] < k:
7 return -1
8
9 # Minimum steps - track from both ends
10 total_steps = n
11 left = right = 0
12 current_count = {'a': 0, 'b': 0, 'c': 0}
13
14 for left in range(n):
15 current_count[s[left]] += 1
16 while all(current_count[char] >= k for char in 'abc'):
17 total_steps = min(total_steps, left + 1 + n - right)
18 current_count[s[right]] -= 1
19 right += 1
20 return total_stepsThis Python solution first checks if it's possible to form 'k' occurrences of each character by counting their frequencies. The two-pointer approach is implemented to keep track of minimal steps needed by effectively sliding a window approach from both ends of the string. Adjust pointers and update current character counts to determine the smallest window, ensuring minimal moves.
This approach involves identifying the largest contiguous subarray that lacks at least 'k' of one or more characters. By calculating the complement of such subarrays, we aim to find the minimal total of minutes required.
Time Complexity: O(n), stemming from a single pass to compute with sliding window technique.
Space Complexity: O(1) as the space needed is independent of the input size.
1import java.util.*;
2
3
The Java implementation calculates the shortest segment where all characters meet the conditions less than `k`. The required length is derived from the complement idea and uses a greedy sliding window strategy to find the maximum length of allowable segments, yielding the minimal minutes required for removal.