Find Substring With Given Hash Value

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16

class Solution:
    def subStrHash(self, s: str, power: int, modulo: int, k: int, hashValue: int) -> str:
        def val(c):
            return ord(c) - ord('a') + 1

        result = n = len(s)
        pk = pow(power, k, modulo)  # Compute power^k mod modulo
        current = 0

        for i in range(n - 1, -1, -1):  # Using Python 3 range instead of xrange
            current = (current * power + val(s[i])) % modulo  # Updating current hash value
            if i + k < n:
                current = (current - val(s[i + k]) * pk) % modulo  # Adjusting for the removed character
            if current == hashValue:
                result = i  # Storing the start index of the matching substring
        return s[result: result + k]

Identifying Problem Isomorphism

“Find Substring With Given Hash Value” can be mapped to “Rabin Karp Algorithm for Pattern Searching”.

The Rabin Karp Algorithm is simpler than the initial problem and provides a foundational understanding of the concept of using hash values in substring searching. Both problems deal with substrings and hash values, using a ‘rolling hash’ technique to efficiently search for a substring within a larger string.

As the difficulty progresses, this problem can also be mapped to the more complex “Minimum Window Substring” problem. This problem is not an exact match but offers a similar theme around substring problems. It builds upon the concept of searching for a substring within a given string but introduces additional constraints around window sizes, thus increasing the complexity.

Both of these mappings offer valuable context and a stepwise increase in complexity for understanding the “Find Substring With Given Hash Value” problem, enhancing your problem-solving abilities and innovating techniques for similar problems.

To tackle the problem “Find Substring With Given Hash Value,” it would be beneficial to understand concepts like sliding window technique, rolling hash, string manipulation and hashing.

10 Prerequisite LeetCode Problems

Here are 10 problems to grasp these concepts:

  1. 3. Longest Substring Without Repeating Characters: A basic problem to understand the sliding window concept.

  2. 30. Substring with Concatenation of All Words: This problem can help you to understand how to deal with substrings.

  3. 76. Minimum Window Substring: Another problem to understand the sliding window concept but with a bit more complexity.

  4. 438. Find All Anagrams in a String: A problem involving searching for anagrams (a sort of substring) within a string.

  5. 567. Permutation in String: This problem can help you to understand how to find permutations of a substring in a string.

  6. 1044. Longest Duplicate Substring: A problem that involves searching for substrings in a string using a binary search and a rolling hash.

  7. 424. Longest Repeating Character Replacement: This problem requires understanding of the sliding window concept and character replacement.

  8. 5. Longest Palindromic Substring: This problem helps in understanding how to find palindromic substrings, which is a different type of substring problem.

  9. 380. Insert Delete GetRandom O(1): This problem helps understand the concept of hashing and the importance of O(1) operations.

  10. 992. Subarrays with K Different Integers: A more advanced sliding window problem, where the window size is not constant.