Longest Repeating Character Replacement
To solve this coding challenge, we'll need to implement a strategy that maintains the length of the longest substring with repeating characters after allowing at most
changes in the characters.
k
Explanation
The problem can be elegantly solved using a sliding window technique. This approach helps manage a dynamic window that can 'slide' over the string, expanding and contracting as needed to find the maximum length of the desired substring. Here's a step-by-step approach to understand how the solution works:- Understanding the Sliding Window :
- We initialize a window that starts at the beginning of the string.
- We will expand the window by including characters from the right.
-
If the condition that the number of characters to be replaced exceeds
is met, we will shrink the window from the left.
k - Character Count Management :
- We need to keep track of the frequency of characters within the current window. This can be managed using a dictionary or a list that tracks occurrences of each character.
- Max Frequency Character :
- Within the current window, keep track of the count of the most frequent character.
-
This helps in determining if the current window length minus the max frequency character is within the allowable replacements (
).
k - Adjusting the Window :
-
If the window length (right - left + 1) minus the count of the most frequent character is greater than
, it signifies we have more than
kcharacters that need replacement. Hence, we should contract the window from the left until the condition is satisfied again.k - Recording the Maximum Length :
- Keep track of the maximum length of such a window during this entire process.
- Initialization :
-
is set to 0 as initially, we haven't found any valid window.
max_length -
is also 0 initially because the window is empty.
max_frequency -
(start of the window) is set to the start of the string.
left_pointer -
is an empty dictionary that will hold the count of characters within the current window.
char_count - Sliding the Window :
-
Loop through the string using a
which marks the end of the current window.
right_pointer -
For each character
, increase its count in
s[right_pointer].char_count -
Update
to be the highest frequency of any character in the current window.
max_frequency - Window Adjustment :
-
If the number of characters to replace within the current window exceeds
, then start shrinking the window from the left by moving
krightward.left_pointer -
Decrement the count of the character at
in
left_pointer.char_count - Recording Maximum Length :
-
Each time the window is adjusted, calculate and update
if the current window is larger than the previously recorded maximum.
max_length
Pseudocode
// Initialize variables
max_length = 0 // To store the length of the longest valid substring found
max_frequency = 0 // To store the count of the most frequently occurring character in the current window
left_pointer = 0 // Start of the current window
char_count = {} // Dictionary to store the frequency of each character in the current window
// Loop through each character in the string using right_pointer
for right_pointer from 0 to len(s) - 1:
// Include character at right_pointer in the window, increment its count
char_count[s[right_pointer]] = char_count.get(s[right_pointer], 0) + 1
// Update max_frequency with the frequency of the most common character in current window
max_frequency = max(max_frequency, char_count[s[right_pointer]])
// Check if current window size minus maximum character frequency is greater than k
if (right_pointer - left_pointer + 1 - max_frequency) > k:
// If condition is true, shrink window from the left
char_count[s[left_pointer]] -= 1
left_pointer += 1
// Calculate and update max_length
max_length = max(max_length, right_pointer - left_pointer + 1)
return max_length