Categorize Box According to Criteria - Practice Coding Problems

Categorize Box According to Criteria - Problem

Math Easy

Given four integers length, width, height, and mass, representing the dimensions and mass of a box, respectively, return a string representing the category of the box.

The box is "Bulky" if:

Any of the dimensions of the box is greater or equal to 10⁴.
Or, the volume of the box is greater or equal to 10⁹.

If the mass of the box is greater or equal to 100, it is "Heavy".

If the box is both "Bulky" and "Heavy", then its category is "Both".

If the box is neither "Bulky" nor "Heavy", then its category is "Neither".

If the box is "Bulky" but not "Heavy", then its category is "Bulky".

If the box is "Heavy" but not "Bulky", then its category is "Heavy".

Note that the volume of the box is the product of its length, width and height.

Input & Output

Example 1 — Heavy Box

$ Input: length = 1000, width = 35, height = 700, mass = 300

› Output: Heavy

💡 Note: Volume = 1000 × 35 × 700 = 24,500,000 < 10⁹, all dimensions < 10⁴, so not bulky. Mass = 300 ≥ 100, so heavy. Result: Heavy.

Example 2 — Bulky Box

$ Input: length = 200, width = 50, height = 800, mass = 50

› Output: Neither

💡 Note: Volume = 200 × 50 × 800 = 8,000,000 < 10⁹, all dimensions < 10⁴, so not bulky. Mass = 50 < 100, so not heavy. Result: Neither.

Example 3 — Both Bulky and Heavy

$ Input: length = 10000, width = 20, height = 30, mass = 150

› Output: Both

💡 Note: Length = 10000 ≥ 10⁴, so bulky. Mass = 150 ≥ 100, so heavy. Both conditions met. Result: Both.

Constraints

1 ≤ length, width, height ≤ 10⁵
1 ≤ mass ≤ 10³

Visualization

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Understanding the Visualization

Input

Box with length=1000, width=35, height=700, mass=300

Evaluation

Check bulky and heavy conditions

Output

Return appropriate category string

Key Takeaway

🎯 Key Insight: Use boolean flags to separately track bulky and heavy conditions, then combine them with simple conditional logic

Asked in

a Amazon 15 G Google 12

This problem requires conditional logic to categorize boxes based on size and weight criteria. The key insight is to use boolean flags to track bulky (dimension ≥ 10⁴ OR volume ≥ 10⁹) and heavy (mass ≥ 100) conditions, then apply simple if-else logic. Best approach uses optimized boolean evaluation. Time: O(1), Space: O(1)

Common Approaches

Approach	Time	Space	Notes
✓ Optimized Boolean Logic	O(1)	O(1)	Use early evaluation and cleaner boolean logic for efficiency
Direct Condition Checking	O(1)	O(1)	Check all conditions directly and return appropriate category

Optimized Boolean Logic — Algorithm Steps

Step 1: Check bulky conditions with short-circuit evaluation
Step 2: Check heavy condition only if needed
Step 3: Use optimized if-else chain for category determination

Visualization

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Step-by-Step Walkthrough

Input

Read box parameters

Short-Circuit Check

Evaluate conditions with early termination

Nested Logic

Use nested ternary operations for cleaner code

Code -

solution.c — C

#include <stdio.h>
#include <string.h>

char* solution(int length, int width, int height, int mass) {
    // Check bulky condition with short-circuit evaluation
    int isBulky = (length >= 10000 || width >= 10000 || height >= 10000 || 
                   (long long)length * width * height >= 1000000000LL);
    
    // Check heavy condition
    int isHeavy = mass >= 100;
    
    // Optimized conditional logic
    if (isBulky) {
        return isHeavy ? "Both" : "Bulky";
    } else {
        return isHeavy ? "Heavy" : "Neither";
    }
}

int main() {
    int length, width, height, mass;
    scanf("%d", &length);
    scanf("%d", &width);
    scanf("%d", &height);
    scanf("%d", &mass);
    
    char* result = solution(length, width, height, mass);
    printf("%s\n", result);
    
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(1)

Fixed number of operations with potential short-circuiting

✓ Linear Growth

Space Complexity

O(1)

Only uses boolean variables and no extra data structures

✓ Linear Space

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Input & Output

Constraints

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Related Problems

Common Approaches

Optimized Boolean Logic — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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