def min_distance(word1: str, word2: str) -> int:
    m, n = len(word1), len(word2)
    dp = [[0] * (n + 1) for _ in range(m + 1)]

    # base cases: converting to/from empty string
    for i in range(m + 1):
        dp[i][0] = i  # delete all chars of word1
    for j in range(n + 1):
        dp[0][j] = j  # insert all chars of word2

    for i in range(1, m + 1):
        for j in range(1, n + 1):
            if word1[i - 1] == word2[j - 1]:
                dp[i][j] = dp[i - 1][j - 1]  # no operation needed
            else:
                dp[i][j] = 1 + min(
                    dp[i - 1][j],      # delete from word1
                    dp[i][j - 1],      # insert into word1
                    dp[i - 1][j - 1]   # replace
                )

    return dp[m][n]

# Time: O(m * n), Space: O(m * n)
# "horse", "ros" -> 3 (horse->rorse->rose->ros)

Dynamic Programming — Common Patterns (Knapsack, LCS)

Dynamic Programming — Common Patterns (Knapsack, LCS)

Dynamic Programming — Common Patterns (Knapsack, LCS)