old_contents: """Minimum Edit Distance (Levenshtein).
  
  Given two words word1 and word2, find the minimum number of operations 
  required to convert word1 to word2.
  
  You have the following 3 operations permitted on a word:
  - Insert a character (to word1)
  - Delete a character (of word1)
  - Replace a character (of word1 & word2)
  
  Operation costs:
  - Standard: If each operation has cost of 1.
  - Levenshtein: If replace operation has cost of 2.
  
  Example 1:
  Input: word1 = "horse", word2 = "ros"
  Output: 3
  Explanation: 
  horse -> rorse (replace 'h' with 'r')
  rorse -> rose (remove 'r')
  rose -> ros (remove 'e')
  
  Example 2:
  Input: word1 = "intention", word2 = "execution"
  Output: 5
  Explanation: 
  intention -> inention (remove 't')
  inention -> enention (replace 'i' with 'e')
  enention -> exention (replace 'n' with 'x')
  exention -> exection (replace 'n' with 'c')
  exection -> execution (insert 'u')
  """
  
  class MinimumEditDistance(object):
  	pass
  
  
  def main():
  	pass
  
  
  if __name__ == '__main__':
  	main()
  
new_contents: class MinimumEditDistance(object):
  	"""Minimum Edit Distance (Levenshtein) with Backtrace.
  
  	Given two strings, find the minimum number of operations required to 
  	convert string1 to string2.
  
  	You have the following 3 operations permitted on a word:
  	- Insert a character (to string1)
  	- Delete a character (of string1)
  	- Substitude a character (of string1 & string2)
  
  	Operation costs:
  	- Standard: If each operation has cost of 1.
  	- Levenshtein: If substitude operation has cost of 2.
  
  	Align each character of the two string1 to each other by keeping a "backtrace".
  
  	Example:
  	Input: string1 = "intention", string2 = "execution"
  	Output: 5
  	inte*ntion
  	*execution
  	----------
  	dss is
  	"""
  	pass
  
  
  def main():
  	pass
  
  
  if __name__ == '__main__':
  	main()
  
subject: Revise docstrring