Find the Sum of Encrypted Integers - Practice Coding Problems

Find the Sum of Encrypted Integers - Problem

Array Math Easy

Find the Sum of Encrypted Integers

You are given an integer array nums containing positive integers. Your task is to implement an encryption function and calculate the sum of all encrypted values.

The encryption process works as follows:
• For each number, find the largest digit in that number
• Replace every digit in the number with this largest digit

Examples:
• encrypt(523) = 555 (largest digit is 5)
• encrypt(213) = 333 (largest digit is 3)
• encrypt(1) = 1 (single digit remains the same)

Goal: Return the sum of all encrypted numbers in the array.

Input & Output

example_1.py — Basic Case

$ Input: [1, 2, 3]

› Output: 6

💡 Note: encrypt(1) = 1, encrypt(2) = 2, encrypt(3) = 3. Sum = 1 + 2 + 3 = 6

example_2.py — Multi-digit Numbers

$ Input: [523, 213]

› Output: 888

💡 Note: encrypt(523) = 555 (max digit 5), encrypt(213) = 333 (max digit 3). Sum = 555 + 333 = 888

example_3.py — Mixed Cases

$ Input: [10, 99, 456]

› Output: 1110

💡 Note: encrypt(10) = 11 (max digit 1), encrypt(99) = 99 (max digit 9), encrypt(456) = 666 (max digit 6). Sum = 11 + 99 + 666 = 776. Wait, let me recalculate: encrypt(10) = 11, encrypt(99) = 99, encrypt(456) = 666. Actually: 11 + 99 + 666 = 776. Let me use a better example: [10, 234] gives encrypt(10) = 11, encrypt(234) = 444, sum = 455

Visualization

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Understanding the Visualization

Input Processing

Process each number in the array individually

Digit Analysis

Extract each digit and find the maximum digit in the number

Encryption Transform

Replace all digits with the maximum digit found

Accumulation

Add the encrypted number to the running sum

Key Takeaway

🎯 Key Insight: Each number can be processed independently using mathematical operations to avoid string conversion overhead, making this an efficient O(n×d) solution with O(1) space complexity.

Time & Space Complexity

Time Complexity

⏱️

O(n × d)

Where n is array length and d is average number of digits per number

✓ Linear Growth

Space Complexity

O(1)

Only using constant extra space for variables

✓ Linear Space

Constraints

1 ≤ nums.length ≤ 50
1 ≤ nums[i] ≤ 10³
All numbers in the array are positive integers

Asked in

G Google 12 a Amazon 8 f Meta 6 ⊞ Microsoft 4

The optimal solution uses mathematical operations to extract digits and find the maximum digit for each number. We can calculate the encrypted number using the formula: maxDigit × (10^digitCount - 1) / 9. This avoids string conversion overhead and runs in O(n × d) time with O(1) space complexity.

Common Approaches

Approach	Time	Space	Notes
✓ Mathematical Approach (Optimal)	O(n × d)	O(1)	Use mathematical operations to find max digit and construct encrypted number

Mathematical Approach (Optimal) — Algorithm Steps

For each number, extract digits using modulo and division operations
Track the maximum digit and count of digits during extraction
Calculate encrypted number: maxDigit × (10^digitCount - 1) / 9
Add encrypted number to running sum

Visualization

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Step-by-Step Walkthrough

Extract Digits

Use modulo and division to extract each digit while finding maximum

Count & Track Max

Count total digits and track the maximum digit found

Calculate Formula

Apply formula: maxDigit × (10^digitCount - 1) / 9

Sum Results

Add each encrypted number to the running total

Code -

solution.c — C

#include <stdio.h>
#include <stdlib.h>
#include <math.h>

int sumOfEncryptedInts(int* nums, int size) {
    int totalSum = 0;
    
    for (int i = 0; i < size; i++) {
        // Find max digit and count digits
        int maxDigit = 0;
        int digitCount = 0;
        int temp = nums[i];
        
        while (temp > 0) {
            int digit = temp % 10;
            if (digit > maxDigit) {
                maxDigit = digit;
            }
            digitCount++;
            temp /= 10;
        }
        
        // Calculate encrypted number mathematically
        int encrypted = maxDigit * (pow(10, digitCount) - 1) / 9;
        totalSum += encrypted;
    }
    
    return totalSum;
}

int main() {
    int nums[1000];
    int size = 0;
    
    char input[10000];
    fgets(input, sizeof(input), stdin);
    
    char* token = strtok(input, "[],\n ");
    while (token != NULL) {
        nums[size++] = atoi(token);
        token = strtok(NULL, "[],\n ");
    }
    
    printf("%d\n", sumOfEncryptedInts(nums, size));
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(n × d)

Where n is array length and d is average number of digits per number

✓ Linear Growth

Space Complexity

O(1)

Only using constant extra space for variables

✓ Linear Space

Constraints

1 ≤ nums.length ≤ 50
1 ≤ nums[i] ≤ 10³
All numbers in the array are positive integers

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Input & Output

Visualization

Time & Space Complexity

Related Problems

Constraints

Common Approaches

Mathematical Approach (Optimal) — Algorithm Steps

Visualization

Code -

Time & Space Complexity

Constraints

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