Given two non-negative integers **N** and **P**, return the number of base-10 numbers with **N** digits and with the digit product equal to **P**

**Example:**

Input:N= 3,P= 6Output:9Explanation:[ 123, 132, 213, 231, 312, 321, 116, 161, 611 ]

N <= 12

The core challenge of this problem is to find all possible numbers with exactly N digits such that the product of their digits equals P. This problem is significant in combinatorial number theory and has applications in cryptography and digital signal processing.

Potential pitfalls include handling cases where P is 0 or 1, as well as ensuring that the numbers have exactly N digits (leading zeros are not allowed).

To solve this problem, we need to generate all possible combinations of N digits and check if their product equals P. A naive solution would involve generating all N-digit numbers and checking each one, but this is not efficient.

Instead, we can use a recursive approach to build the numbers digit by digit, ensuring that the product of the digits remains equal to P. This reduces the number of combinations we need to check.

The naive solution involves generating all N-digit numbers and checking if their product equals P. This approach is not optimal due to its high time complexity.

We can use a recursive backtracking approach to build the numbers. This method is more efficient as it prunes the search space by stopping early if the product exceeds P or if the number of digits exceeds N.

Here is a step-by-step breakdown of the recursive backtracking algorithm:

- Start with an empty number and a product of 1.
- At each step, add a digit from 1 to 9 to the number.
- Update the product and the number of digits.
- If the product equals P and the number of digits equals N, count this number as a valid solution.
- If the product exceeds P or the number of digits exceeds N, backtrack.
- Repeat until all combinations are checked.

```
import java.util.ArrayList;
import java.util.List;
public class DigitProduct {
// Function to find all N-digit numbers with digit product P
public static int findNumbersWithDigitProduct(int N, int P) {
List<String> result = new ArrayList<>();
findNumbers(N, P, 1, "", result);
return result.size();
}
// Helper function to perform recursive backtracking
private static void findNumbers(int N, int P, int currentProduct, String currentNumber, List<String> result) {
// Base case: if the number has N digits and the product is P
if (currentNumber.length() == N) {
if (currentProduct == P) {
result.add(currentNumber);
}
return;
}
// Try adding digits from 1 to 9
for (int digit = 1; digit <= 9; digit++) {
// Calculate new product
int newProduct = currentProduct * digit;
// If the new product is less than or equal to P, continue
if (newProduct <= P) {
findNumbers(N, P, newProduct, currentNumber + digit, result);
}
}
}
public static void main(String[] args) {
int N = 3;
int P = 6;
System.out.println("Number of " + N + "-digit numbers with digit product " + P + ": " + findNumbersWithDigitProduct(N, P));
}
}
```

The time complexity of the optimized solution is O(9^N) in the worst case, as we try each digit from 1 to 9 for each of the N positions. However, the actual number of recursive calls is much lower due to the pruning of invalid paths.

The space complexity is O(N) due to the recursion stack and the storage of the current number being built.

Potential edge cases include:

- P = 0: No valid numbers except for the case where N = 1 and the number is 0.
- P = 1: Only valid numbers are those with digits 1 (e.g., 111 for N = 3).
- N = 1: The number itself must be equal to P.

These cases are handled by the recursive approach, which ensures that only valid numbers are counted.

To test the solution comprehensively, include a variety of test cases:

- Simple cases: N = 1, P = 1; N = 2, P = 2.
- Edge cases: N = 1, P = 0; N = 3, P = 0.
- Complex cases: N = 3, P = 6; N = 4, P = 24.

Use a testing framework like JUnit to automate the testing process.

When approaching such problems, consider the following tips:

- Break down the problem into smaller sub-problems.
- Use recursive backtracking to explore all possible solutions.
- Prune the search space to improve efficiency.
- Practice similar problems to improve problem-solving skills.

Understanding and solving combinatorial problems like this one is crucial for developing strong problem-solving skills. Practice and exploration of different approaches are key to mastering such problems.

For further reading and practice, consider the following resources:

- LeetCode - Practice coding problems.
- GeeksforGeeks - Tutorials and problem-solving tips.
- Coursera - Online courses on algorithms and data structures.