algoadvance

We are given two strings s and t. We need to determine whether there exists any substring of t that is also a substring of s or the reverse of s.

Return a boolean value: True if there’s at least one such substring and False otherwise.

Clarifying Questions

1. Lengths of Strings: What are the lengths of strings s and t?
2. Case Sensitivity: Do the comparisons need to be case-sensitive?
3. Character Set: Do the strings contain only ASCII characters?

Strategy

1. Reverse s: Compute the reverse of string s.
2. Set of Substrings: Generate all possible substrings of t and check if any of these substrings exist in s or the reversed s.
3. Optimization: Instead of generating all substrings of t, we can use the inherent Python string operations to check if one of the substrings is in s or its reverse.

Code

The following Python code implements the above strategy:

def check_substring_existence(s: str, t: str) -> bool:
    reversed_s = s[::-1]
    
    # Check all substrings of t
    for i in range(len(t)):
        for j in range(i + 1, len(t) + 1):
            substr = t[i:j]
            if substr in s or substr in reversed_s:
                return True
            
    return False

# Example Usage
s = "hello"
t = "world"
print(check_substring_existence(s, t))  # Example output: False

Time Complexity

• Reversal of String: Reversing the string s will take O(n), where n is the length of s.
• Substring Checks: We check all substrings of t, which has a time complexity of O(m^3) due to the nested loops and the in check for each substring, where m is the length of t.

Overall, while the reverse operation is O(n), the dominant factor is the O(m^3) substring checks. If m and n are the same length, the overall complexity is O(m^3). This is acceptable for small strings, but for larger strings, optimization techniques like suffix trees or Knuth-Morris-Pratt (KMP) algorithm might be considered.

Try our interview co-pilot at AlgoAdvance.com

• Got blindsided by a question you didn’t expect?

• Spend too much time studying?

• Or simply don’t have the time to go over all 3000 questions?