What is the optimal time complexity of solving Strong number?

The optimized solution achieves a time complexity of O(n) by using sorting, mathematical shortcuts, or hash table lookups.

What is the auxiliary space complexity for Strong number?

The space complexity is O(1) since we only use a minimal/constant amount of extra memory for tracking variables (or auxiliary space if dynamic structures are allocated).

What are the typical edge cases we must handle in Strong number?

Key edge cases include empty collections, negative or large bounds causing integer overflow, arrays with only one element, or inputs where target criteria are not met.

How can we optimize the brute force approach for Strong number?

Brute force methods often inspect all possible combinations. We optimize this by sorting the input list to enable binary search, or tracking processed items in a set to avoid redundant nested loop lookups.

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Python BasicsEasy

Strong number

Learn how to solve the 'Strong number' problem. This detailed resource details brute force and optimized approaches.

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Problem Statement

Easy

Write a function is_strong(n) that takes a positive integer n and returns True if it is a Strong number, or False otherwise. A Strong number is a number where the sum of the factorials of its individual digits equals the number itself. For example, 145 = 1! + 4! + 5! = 1 + 24 + 120 = 145.

Constraints

•1 <= n <= 10^6

Examples

Example 1

Input

n = 145

Output

True

Explanation

1! + 4! + 5! = 1 + 24 + 120 = 145, which equals n.

Example 2

Input

n = 2

Output

True

Explanation

2! = 2, which equals n.

Example 3

Input

n = 123

Output

False

Explanation

1! + 2! + 3! = 1 + 2 + 6 = 9, which is not 123.

Need a Hint?

Use simple arithmetic operators (like modulo `%`, division `//`), conditional checks, or loops to inspect number properties.

Edge Cases to Watch

Empty list or null input variables
Single item lists/arrays
Extremely large input bounds causing integer or stack overflow

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