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
k
changes in the characters.

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:
  1. 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
      k
      is met, we will shrink the window from the left.
  2. 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.
  3. 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
      ).
  4. Adjusting the Window :
    • If the window length (right - left + 1) minus the count of the most frequent character is greater than
      k
      , it signifies we have more than
      k
      characters that need replacement. Hence, we should contract the window from the left until the condition is satisfied again.
  5. Recording the Maximum Length :
    • Keep track of the maximum length of such a window during this entire process.

    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
    
                                            

    Step-by-Step Explanation

  6. Initialization :
    • max_length
      is set to 0 as initially, we haven't found any valid window.
    • max_frequency
      is also 0 initially because the window is empty.
    • left_pointer
      (start of the window) is set to the start of the string.
    • char_count
      is an empty dictionary that will hold the count of characters within the current window.
  7. Sliding the Window :
    • Loop through the string using a
      right_pointer
      which marks the end of the current window.
    • For each character
      s[right_pointer]
      , increase its count in
      char_count
      .
    • Update
      max_frequency
      to be the highest frequency of any character in the current window.
  8. Window Adjustment :
    • If the number of characters to replace within the current window exceeds
      k
      , then start shrinking the window from the left by moving
      left_pointer
      rightward.
    • Decrement the count of the character at
      left_pointer
      in
      char_count
      .
  9. Recording Maximum Length :
    • Each time the window is adjusted, calculate and update
      max_length
      if the current window is larger than the previously recorded maximum.
This process continues until the entire string has been processed and ensures that the solution is optimal and efficient in terms of time complexity.