What is the time complexity of Largest 3-Same-Digit Number in String?

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

What data structures are used to solve Largest 3-Same-Digit Number in String?

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

What are the key insights for solving Largest 3-Same-Digit Number in String?

Insight 1: Iterating through the string using a sliding window of size 3 is efficient to check all possible substrings of length 3. Insight 2: String comparison using '>' operator in Python/Java/C++ directly handles lexicographical comparison, which correctly determines the largest integer.

Which companies ask LeetCode 2264. Largest 3-Same-Digit Number in String in interviews?

This problem is frequently asked at PayPay, opentext.

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Largest 3-Same-Digit Number in String - LeetCode 2264 Solution

Largest 3-Same-Digit Number in String - Complete Solution Guide

Largest 3-Same-Digit Number in String is LeetCode problem 2264, a Easy level challenge. This complete guide provides step-by-step explanations, multiple solution approaches, and optimized code in python3, java, cpp.

Problem Statement

You are given a string num representing a large integer. An integer is good if it meets the following conditions: It is a substring of num with length 3 . It consists of only one unique digit. Return the maximum good integer as a string or an empty string "" if no such integer exists . Note: A substring is a contiguous sequence of characters within a string. There may be leading zeroes in num or a good integer. Example 1: Input: num = "6 777 133339" Output: "777" Explanation: There are two disti

Detailed Explanation

The problem asks you to find the largest substring of length 3 within a given string that consists of only one unique digit. For example, in the string "6777133339", the substrings "777" and "333" meet this criteria. The function should return the largest of these 'good' integers as a string. If no such substring exists, it should return an empty string "". The input is a string representing a large integer, and the output is a string representing the largest good integer found or an empty string.

Solution Approach

The provided solutions use a sliding window approach. They iterate through the input string `num`, checking each substring of length 3. For each substring, it verifies if all three characters are identical. If they are, it compares the substring to the current maximum good integer found so far. If the current substring is larger, it updates the maximum. Finally, the function returns the maximum good integer found.

Step-by-Step Algorithm

Step 1: Initialize a variable (e.g., `max_good`) to store the largest good integer found so far. This is initialized to an empty string.
Step 2: Iterate through the input string `num` using a loop that stops three characters before the end of the string.
Step 3: Extract a substring of length 3 starting at the current index.
Step 4: Check if the three characters in the substring are identical. This can be done efficiently by comparing the first character to the second and the second to the third.
Step 5: If the characters are identical (the substring is a good integer), compare it to the current `max_good`. If it's larger, update `max_good`.
Step 6: After iterating through all substrings, return `max_good`.

Key Insights

Insight 1: Iterating through the string using a sliding window of size 3 is efficient to check all possible substrings of length 3.
Insight 2: String comparison using '>' operator in Python/Java/C++ directly handles lexicographical comparison, which correctly determines the largest integer.
Insight 3: Handling the edge case where no good integer exists (returning an empty string) is crucial. The provided solutions elegantly handle this by initializing a variable (max_good, maxGoodInteger, ans) to an empty string.

Complexity Analysis

Time Complexity: O(n)

Space Complexity: O(1)

Topics

This problem involves: String.

Companies

Asked at: PayPay, opentext.

Largest 3-Same-Digit Number in String | LeetCode 2264

Easy

String

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

Solution Code

Available in:

class Solution {
    public String largestGoodInteger(String num) {
        String maxGoodInteger = "";
        for (int i = 0; i <= num.length() - 3; i++) {
            String sub = num.substring(i, i + 3);
            if (sub.charAt(0) == sub.charAt(1) && sub.charAt(1) == sub.charAt(2)) {
                if (maxGoodInteger.compareTo(sub) < 0) {
                    maxGoodInteger = sub;
                }
            }
        }
        return maxGoodInteger;
    }
}

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Problem Info

Description

Problem 2264: Largest 3-Same-Digit Number in String - Detailed explanation and solution approaches.

Topics

String

Companies

PayPayopentext

Stats

Difficulty:Easy

Languages:3

Companies:2

Problem #:2264

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

6 steps

1
Step 1: Initialize a variable (e.g., `max_good`) to store the largest good integer found so far. This is initialized to an empty string.
2
Step 2: Iterate through the input string `num` using a loop that stops three characters before the end of the string.
3
Step 3: Extract a substring of length 3 starting at the current index.
4
Step 4: Check if the three characters in the substring are identical. This can be done efficiently by comparing the first character to the second and the second to the third.
5
Step 5: If the characters are identical (the substring is a good integer), compare it to the current `max_good`. If it's larger, update `max_good`.
6
Step 6: After iterating through all substrings, return `max_good`.

💡

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(n)

👍 Linear - Good! Visits each element once.

💾

Space Complexity

O(1)

💪 Constant space - Uses same memory regardless of input!

📝

Why?

The time complexity is O(n) because the algorithm iterates through the input string once. The space complexity is O(1) because only a constant amount of extra space is used to store variables like `max_good`, regardless of the input size. The substring operation in Python/Java/C++ is optimized for this use case and does not contribute significantly to space complexity.

📖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 Expression

A regular expression could be used to find all occurrences of three consecutive identical digits. Then, the largest match could be selected.

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

Trade-offs: While potentially more concise, regular expressions might be less efficient than the sliding window approach in some implementations. The readability might also be reduced for beginners.

✨

Key Insights

1Insight 1: Iterating through the string using a sliding window of size 3 is efficient to check all possible substrings of length 3.
2Insight 2: String comparison using '>' operator in Python/Java/C++ directly handles lexicographical comparison, which correctly determines the largest integer.
3Insight 3: Handling the edge case where no good integer exists (returning an empty string) is crucial. The provided solutions elegantly handle this by initializing a variable (max_good, maxGoodInteger, ans) to an empty string.

📚

Key Terms Explained

For Students

String

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

Edge Cases

Edge case 1: Empty input string. The solution correctly handles this by returning an empty string.
Edge case 2: No good integers found in the string. The solution correctly returns an empty string in this case.

⚠️

Common Mistakes to Avoid

✗Common mistake 1: Incorrectly handling the case where no good integer exists. Forgetting to initialize `max_good` to an empty string or failing to return an empty string when no good integers are found.

✗Common mistake 2: Inefficiently checking if the three characters are identical. Using nested loops or unnecessary comparisons instead of a simple comparison of the first and second, and second and third characters.

✅

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: Data validation or cleaning. This algorithm could be used to identify and potentially correct errors in data sets containing numerical sequences.

🏦Real-world scenario 2: Pattern recognition in sensor data or time series analysis. Finding recurring patterns of three identical values might indicate a specific event or state.

💡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

Don't rush. Explain your thought process clearly. Easy problems are often about communication.

⚠️ 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 13, 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

In a real interview, always clarify constraints first. Ask about input size and value ranges.

@TechLeadJul 14

Don't forget to handle the edge case when the input is empty. Many candidates miss this in interviews.

@DevExpert92Jul 7

❓

Frequently Asked Questions

How do I handle string manipulation efficiently?

In languages with immutable strings (Java, Python, C#), use StringBuilder/list to avoid O(n) concatenation cost. Consider using character arrays for in-place modifications. For pattern matching, consider KMP or Rabin-Karp for O(n+m) complexity.

How should I approach easy-level algorithm problems?

Easy problems build foundational skills. Focus on: 1) Understanding the problem completely before coding, 2) Writing clean, readable code, 3) Handling all edge cases (empty input, single element, etc.), 4) Analyzing time and space complexity. Don't skip complexity analysis even for simple solutions.

How should I practice algorithm problems effectively?

Focus on understanding patterns rather than memorizing solutions. After solving a problem, review optimal solutions and understand the intuition. Group similar problems to recognize patterns. Practice explaining your approach out loud. Review problems after a few days to test retention.

What is the optimal approach for "Largest 3-Same-Digit Number in String"?

For this easy-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.

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