Solution Explanation: Masking Personal Information

This problem involves masking personal information, specifically email addresses and phone numbers, according to specific rules. The solution efficiently determines the type of information (email or phone number) and applies the appropriate masking technique.

Approach

The core idea is to first identify whether the input string s represents an email address or a phone number. This is determined by checking if the string contains the "@" symbol. If it does, it's treated as an email; otherwise, it's considered a phone number.

Email Masking:

1. Lowercase Conversion: The entire email is converted to lowercase.
2. Name Masking: The name part (before the "@") is masked by replacing all characters except the first and last with asterisks ("*****").
3. Return Masked Email: The masked name is combined with the domain part (after the "@") to construct the masked email string.

Phone Number Masking:

1. Digit Extraction: All non-digit characters are removed from the phone number string.
2. Country Code Determination: The length of the resulting digit string determines the country code length (number of digits before the last 10).
3. Masking Format: Based on the country code length, a specific masking format is applied. The last four digits remain unchanged ("XXXX"), while the preceding digits are replaced with asterisks and hyphens.
4. Return Masked Number: The masked phone number string is returned.

Time and Space Complexity

Time Complexity: O(n), where n is the length of the input string s. This is because the algorithms iterate through the string a constant number of times to perform operations like lowercase conversion, digit extraction, and masking. The operations involved have linear time complexity.

Space Complexity: O(n) in the worst case. This is because we might create intermediate strings during the masking process (e.g., to store the lowercase version of the email or the extracted digits from the phone number), and the size of these intermediate strings is proportional to the length of the input string.

Code Implementation (Python)

The Python code efficiently implements the above approach:

class Solution:
    def maskPII(self, s: str) -> str:
        if "@" in s:  # Email
            s = s.lower()
            at_index = s.index("@")
            name = s[:at_index]
            domain = s[at_index:]
            masked_name = name[0] + "*" * (len(name) - 2) + name[-1] if len(name) > 2 else name
            return masked_name + domain
        else:  # Phone Number
            digits = "".join(c for c in s if c.isdigit())
            country_code_len = len(digits) - 10
            local_number = digits[-4:]
            masked_number = "+" + "*" * country_code_len + "-" + "***-***-" + local_number if country_code_len > 0 else "***-***-" + local_number
            return masked_number
 

The code is concise and readable, clearly demonstrating the steps involved in identifying the information type and applying the respective masking rules. Other languages (Java, C++, Go, TypeScript) provide similar implementations following the same algorithmic approach. The key is to efficiently handle both email and phone number masking within a single function.