What is the time complexity of Masking Personal Information?

The optimal solution has a time complexity of O(1).

What data structures are used to solve Masking Personal Information?

This problem uses String. Understanding these concepts is essential for solving this Medium problem efficiently.

What are the key insights for solving Masking Personal Information?

Insight 1: The problem can be solved by straightforward string manipulation and conditional logic, separating the email and phone number processing based on the presence of the '@' character. Insight 2: Regular expressions can be used to remove non-digit characters from phone numbers.

Which companies ask LeetCode 831. Masking Personal Information in interviews?

This problem is frequently asked at X.

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Masking Personal Information - LeetCode 831 Solution

Masking Personal Information - Complete Solution Guide

Masking Personal Information is LeetCode problem 831, a Medium level challenge. This complete guide provides step-by-step explanations, multiple solution approaches, and optimized code in python3, java, cpp, c.

Problem Statement

You are given a personal information string s , representing either an email address or a phone number . Return the masked personal information using the below rules . Email address: An email address is: A name consisting of uppercase and lowercase English letters, followed by The '@' symbol, followed by The domain consisting of uppercase and lowercase English letters with a dot '.' somewhere in the middle (not the first or last character). To mask an email: The uppercase letters in the name and

Detailed Explanation

The problem requires masking personal information, specifically email addresses and phone numbers, according to defined rules. For email addresses, the username and domain are converted to lowercase, the middle characters of the username are replaced with asterisks. For phone numbers, separation characters are removed, and the number is masked based on the number of digits, indicating the country code. The last four digits of the local number are always revealed.

Solution Approach

The solution determines whether the input string is an email or phone number based on the presence of the '@' character. For emails, it converts the string to lowercase, splits it into username and domain, masks the username, and concatenates the parts. For phone numbers, it removes non-digit characters, determines the country code length, and masks the number accordingly.

Step-by-Step Algorithm

Step 1: Check if the input string `s` contains the character '@'. If it does, process it as an email; otherwise, process it as a phone number.
Step 2: If it's an email, convert `s` to lowercase.
Step 3: Split the email into `name` and `domain` using the '@' character as the delimiter.
Step 4: Mask the `name` by taking the first and last characters and replacing the characters in between with five asterisks: `name[0] + '*****' + name[-1]`.
Step 5: Concatenate the masked `name`, '@', and the `domain` to form the masked email.
Step 6: If it's a phone number, remove all non-digit characters from `s`.
Step 7: Determine the number of digits in the cleaned phone number.
Step 8: Extract the last four digits of the phone number.
Step 9: Based on the number of digits, construct the masked phone number string. If the number of digits is 10, the masked string is `***-***-{last four digits}`. If the number of digits is greater than 10, calculate the country code length and mask it with asterisks accordingly e.g., `+{country code mask}-***-***-{last four digits}`.

Key Insights

Insight 1: The problem can be solved by straightforward string manipulation and conditional logic, separating the email and phone number processing based on the presence of the '@' character.
Insight 2: Regular expressions can be used to remove non-digit characters from phone numbers.
Insight 3: The country code length determines the specific masking pattern for phone numbers; careful consideration is needed to handle different country code lengths.

Complexity Analysis

Time Complexity: O(1)

Space Complexity: O(1)

Topics

This problem involves: String.

Companies

Asked at: X.

Masking Personal Information | LeetCode 831

Medium

String

Time: O(1)Space: O(1)

Solution Code

Available in:

class Solution {
    public String maskPII(String s) {
        if (s.indexOf('@') != -1) {
            s = s.toLowerCase();
            String[] parts = s.split("@");
            String name = parts[0];
            String domain = parts[1];
            return name.charAt(0) + "*****" + name.charAt(name.length() - 1) + "@" + domain;
        } else {
            String digits = s.replaceAll("[^0-9]", "");
            int numDigits = digits.length();
            String lastFour = digits.substring(numDigits - 4);

            if (numDigits == 10) {
                return "***-***-" + lastFour;
            } else {
                int countryCodeLen = numDigits - 10;
                String countryCodeMask = "";
                for (int i = 0; i < countryCodeLen; i++) {
                    countryCodeMask += "*";
                }
                return "+" + countryCodeMask + "-***-***-" + lastFour;
            }
        }
    }
}

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Problem Info

Description

Problem 831: Masking Personal Information - Detailed explanation and solution approaches.

Topics

String

Companies

Stats

Difficulty:Medium

Languages:4

Companies:1

Problem #:831

Problem Explanation

💡

Think Before You Code

🤔 Ask Yourself

→What is the input? What output do I need?
→Can I solve a smaller version of this problem first?
→What patterns have I seen in similar problems?

✏️ Try This First

Before looking at the solution, try to solve it on paper with a simple example!

🚀 Try on LeetCode

Solution Approach

📋

Step-by-Step Solution

9 steps

1
Step 1: Check if the input string `s` contains the character '@'. If it does, process it as an email; otherwise, process it as a phone number.
2
Step 2: If it's an email, convert `s` to lowercase.
3
Step 3: Split the email into `name` and `domain` using the '@' character as the delimiter.
4
Step 4: Mask the `name` by taking the first and last characters and replacing the characters in between with five asterisks: `name[0] + '*****' + name[-1]`.
5
Step 5: Concatenate the masked `name`, '@', and the `domain` to form the masked email.
6
Step 6: If it's a phone number, remove all non-digit characters from `s`.
7
Step 7: Determine the number of digits in the cleaned phone number.
8
Step 8: Extract the last four digits of the phone number.
9
Step 9: Based on the number of digits, construct the masked phone number string. If the number of digits is 10, the masked string is `***-***-{last four digits}`. If the number of digits is greater than 10, calculate the country code length and mask it with asterisks accordingly e.g., `+{country code mask}-***-***-{last four digits}`.

💡

Pro Tip for Students

Try tracing through each step with a small example on paper before coding. Understanding "why" each step happens is more important than memorizing the code!

⚡

Complexity Analysis

⏱️

Time Complexity

O(1)

⚡ Constant time - Super fast! Same speed regardless of input size.

💾

Space Complexity

O(1)

💪 Constant space - Uses same memory regardless of input!

📝

Why?

The operations performed are primarily string manipulations like splitting and concatenating. The length of the string is constrained, therefore, the number of operations performed is bounded by a constant. Thus, the time complexity is O(1). The space used by the variables to store results is also independent of the input size. Hence the space complexity is O(1).

📖New to Big O? Click to learn more

Big O Notation - Quick Guide

O(1)Best - Instant

O(log n)Excellent - Binary Search

O(n)Good - One loop

O(n log n)OK - Sorting

O(n²)Slow - Nested loops

O(2ⁿ)Very Slow - Recursion

Alternative Approaches

Regular Expressions

Use regular expressions to extract digits from the phone number string. This might improve readability and conciseness.

Time: O(n) where n is the length of the input string. Regex matching can take linear time.Space: O(1)

Trade-offs: Regular expressions can be slightly slower than iterative character checking but offer better readability and maintainability in some cases.

✨

Key Insights

1Insight 1: The problem can be solved by straightforward string manipulation and conditional logic, separating the email and phone number processing based on the presence of the '@' character.
2Insight 2: Regular expressions can be used to remove non-digit characters from phone numbers.
3Insight 3: The country code length determines the specific masking pattern for phone numbers; careful consideration is needed to handle different country code lengths.

📚

Key Terms Explained

For Students

String

A sequence of characters. Like a word or sentence in programming!

Edge Cases

Edge case 1: Email address with a short username (e.g., '[email protected]'). The username still has 5 asterisks in the middle, even if the name is only 2 characters long. The solution correctly handles this.
Edge case 2: Phone number with the maximum number of digits (13) and separators, The solution correctly extracts only digits and determines the appropriate country code mask.
Edge case 3: Phone number with mixed separator formats. The solution correctly removes all separators before processing the number.

⚠️

Common Mistakes to Avoid

✗Common mistake 1: Incorrectly determining the length of the country code, leading to wrong masking of the phone number.

✗Common mistake 2: Failing to remove all separation characters from the phone number before processing it.

✗Common mistake 3: Not handling edge cases where usernames are very short, leading to incorrect masking.

✅

Learning Tip

Every mistake is a learning opportunity! When you make an error, understand why it happened before moving on.

🌍

Where is This Used in Real Life?

💼Real-world scenario 1: Masking sensitive data in databases or logs to protect user privacy. This algorithm can be used to obfuscate email addresses and phone numbers while still allowing for data analysis or debugging.

🏦Real-world scenario 2: Displaying masked contact information on websites or mobile applications to protect user privacy while still providing a way to contact the user.

💡Understanding real-world applications helps you see the "why" behind algorithms. It's not just about passing interviews—these concepts power the apps and websites you use every day!

Author's Notes

💡 Key Insight

String problems often involve sliding windows or two pointers. Consider if the character set is limited (lowercase letters = only 26 possibilities).

🎯 Interview Tip

Medium problems are the bread and butter of technical interviews. Practice explaining your approach before coding.

⚠️ Watch Out

Mutating strings directly in languages where strings are immutable. Use StringBuilder or arrays.

Written by Saswata Mondal

Software Engineer • Algorithms Enthusiast • Interview Coach

👨‍💻

About the Author

👨‍💻

Saswata MondalAuthor400+ LC Problems

B.Tech CSE, IEM Kolkata | LeetCode Rating: 1672 (Top 15%)

Certified: IBM Java Developer, NPTEL Programming in Java

Last updated: September 20, 2024LeetCode Profile GitHub

This solution has been crafted based on my experience solving 400+ LeetCode problems. Each explanation is designed to help you understand the underlying concepts, not just memorize the code.

Community Tips & Insights

The key insight here is recognizing the pattern. Once you see it, the solution becomes straightforward.

@AlgoMasterJul 14

I was asked this exact problem at my Google interview. The interviewer wanted me to optimize space complexity.

@InterviewProJul 7

Try solving this without using extra space first. It's a great exercise for understanding the underlying pattern.

@CodeNinjaJun 30

❓

Frequently Asked Questions

What is the sliding window technique for string problems?

Sliding window maintains a "window" of characters with two pointers. Expand the right pointer to include characters, shrink from left when window violates constraints. Useful for substring problems, anagrams, and longest/shortest substring with properties.

How much time should I spend on a medium problem in interviews?

In a 45-minute interview, aim for: 5-10 minutes understanding and clarifying, 5-10 minutes discussing approach, 20-25 minutes coding, and 5-10 minutes testing. If stuck after 15 minutes of thinking, verbalize your thought process and ask for hints.

What is the importance of time and space complexity analysis?

Complexity analysis is crucial because: 1) Interviewers always ask about it, 2) It helps you choose between approaches, 3) It demonstrates CS fundamentals. Always state both time and space complexity, and be prepared to explain how you derived them.

What is the optimal approach for "Masking Personal Information"?

For this medium-level String problem, the key is to identify the core pattern. Analyze the input constraints to determine acceptable time complexity. Consider whether standard techniques can optimize the solution. Always handle edge cases and validate your approach with examples before coding.

🤖 Need help with this problem?