LeetCode #3317 — HARD

Find the Number of Possible Ways for an Event

Break down a hard problem into reliable checkpoints, edge-case handling, and complexity trade-offs.

The Problem

Problem Statement

You are given three integers n, x, and y.

An event is being held for n performers. When a performer arrives, they are assigned to one of the x stages. All performers assigned to the same stage will perform together as a band, though some stages might remain empty.

After all performances are completed, the jury will award each band a score in the range [1, y].

Return the total number of possible ways the event can take place.

Since the answer may be very large, return it modulo 10⁹ + 7.

Note that two events are considered to have been held differently if either of the following conditions is satisfied:

Any performer is assigned a different stage.
Any band is awarded a different score.

Example 1:

Input: n = 1, x = 2, y = 3

Output: 6

Explanation:

There are 2 ways to assign a stage to the performer.
The jury can award a score of either 1, 2, or 3 to the only band.

Example 2:

Input: n = 5, x = 2, y = 1

Output: 32

Explanation:

Each performer will be assigned either stage 1 or stage 2.
All bands will be awarded a score of 1.

Example 3:

Input: n = 3, x = 3, y = 4

Output: 684

Constraints:

1 <= n, x, y <= 1000

Step 01

Brute Force Baseline

Problem summary: You are given three integers n, x, and y. An event is being held for n performers. When a performer arrives, they are assigned to one of the x stages. All performers assigned to the same stage will perform together as a band, though some stages might remain empty. After all performances are completed, the jury will award each band a score in the range [1, y]. Return the total number of possible ways the event can take place. Since the answer may be very large, return it modulo 109 + 7. Note that two events are considered to have been held differently if either of the following conditions is satisfied: Any performer is assigned a different stage. Any band is awarded a different score.

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: Math · Dynamic Programming

Example 1

1
2
3

Example 2

5
2
1

Example 3

3
3
4

Core Insight

What unlocks the optimal approach

Fix the number of stages.
Assign the Performers to the stages.
Use inclusion-exclusion to ensure that no stage has 0 performers.

Interview move: turn each hint into an invariant you can check after every iteration/recursion step.

Step 03

Algorithm Walkthrough

Iteration Checklist

Define state (indices, window, stack, map, DP cell, or recursion frame).
Apply one transition step and update the invariant.
Record answer candidate when condition is met.
Continue until all input is consumed.

Use the first example testcase as your mental trace to verify each transition.

Step 04

Edge Cases

Minimum Input

Single element / shortest valid input

Validate boundary behavior before entering the main loop or recursion.

Duplicates & Repeats

Repeated values / repeated states

Decide whether duplicates should be merged, skipped, or counted explicitly.

Extreme Constraints

Largest constraint values

Re-check complexity target against constraints to avoid time-limit issues.

Invalid / Corner Shape

Empty collections, zeros, or disconnected structures

Handle special-case structure before the core algorithm path.

Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #3317: Find the Number of Possible Ways for an Event
class Solution {
    public int numberOfWays(int n, int x, int y) {
        final int mod = (int) 1e9 + 7;
        long[][] f = new long[n + 1][x + 1];
        f[0][0] = 1;
        for (int i = 1; i <= n; ++i) {
            for (int j = 1; j <= x; ++j) {
                f[i][j] = (f[i - 1][j] * j % mod + f[i - 1][j - 1] * (x - (j - 1) % mod)) % mod;
            }
        }
        long ans = 0, p = 1;
        for (int j = 1; j <= x; ++j) {
            p = p * y % mod;
            ans = (ans + f[n][j] * p) % mod;
        }
        return (int) ans;
    }
}

// Accepted solution for LeetCode #3317: Find the Number of Possible Ways for an Event
func numberOfWays(n int, x int, y int) int {
	const mod int = 1e9 + 7
	f := make([][]int, n+1)
	for i := range f {
		f[i] = make([]int, x+1)
	}
	f[0][0] = 1
	for i := 1; i <= n; i++ {
		for j := 1; j <= x; j++ {
			f[i][j] = (f[i-1][j]*j%mod + f[i-1][j-1]*(x-(j-1))%mod) % mod
		}
	}
	ans, p := 0, 1
	for j := 1; j <= x; j++ {
		p = p * y % mod
		ans = (ans + f[n][j]*p%mod) % mod
	}
	return ans
}

# Accepted solution for LeetCode #3317: Find the Number of Possible Ways for an Event
class Solution:
    def numberOfWays(self, n: int, x: int, y: int) -> int:
        mod = 10**9 + 7
        f = [[0] * (x + 1) for _ in range(n + 1)]
        f[0][0] = 1
        for i in range(1, n + 1):
            for j in range(1, x + 1):
                f[i][j] = (f[i - 1][j] * j + f[i - 1][j - 1] * (x - (j - 1))) % mod
        ans, p = 0, 1
        for j in range(1, x + 1):
            p = p * y % mod
            ans = (ans + f[n][j] * p) % mod
        return ans

// Accepted solution for LeetCode #3317: Find the Number of Possible Ways for an Event
// Rust example auto-generated from java reference.
// Replace the signature and local types with the exact LeetCode harness for this problem.
impl Solution {
    pub fn rust_example() {
        // Port the logic from the reference block below.
    }
}

// Reference (java):
// // Accepted solution for LeetCode #3317: Find the Number of Possible Ways for an Event
// class Solution {
//     public int numberOfWays(int n, int x, int y) {
//         final int mod = (int) 1e9 + 7;
//         long[][] f = new long[n + 1][x + 1];
//         f[0][0] = 1;
//         for (int i = 1; i <= n; ++i) {
//             for (int j = 1; j <= x; ++j) {
//                 f[i][j] = (f[i - 1][j] * j % mod + f[i - 1][j - 1] * (x - (j - 1) % mod)) % mod;
//             }
//         }
//         long ans = 0, p = 1;
//         for (int j = 1; j <= x; ++j) {
//             p = p * y % mod;
//             ans = (ans + f[n][j] * p) % mod;
//         }
//         return (int) ans;
//     }
// }

// Accepted solution for LeetCode #3317: Find the Number of Possible Ways for an Event
function numberOfWays(n: number, x: number, y: number): number {
    const mod = BigInt(10 ** 9 + 7);
    const f: bigint[][] = Array.from({ length: n + 1 }, () => Array(x + 1).fill(0n));
    f[0][0] = 1n;
    for (let i = 1; i <= n; ++i) {
        for (let j = 1; j <= x; ++j) {
            f[i][j] = (f[i - 1][j] * BigInt(j) + f[i - 1][j - 1] * BigInt(x - (j - 1))) % mod;
        }
    }
    let [ans, p] = [0n, 1n];
    for (let j = 1; j <= x; ++j) {
        p = (p * BigInt(y)) % mod;
        ans = (ans + f[n][j] * p) % mod;
    }
    return Number(ans);
}

Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Custom checkpoints (one per line)

Press Step or Run All to begin.

Step 07

Complexity Analysis

Time

O(n × x)

Space

O(n × x)

Approach Breakdown

RECURSIVE

O(2ⁿ) time

O(n) space

Pure recursion explores every possible choice at each step. With two choices per state (take or skip), the decision tree has 2ⁿ leaves. The recursion stack uses O(n) space. Many subproblems are recomputed exponentially many times.

DYNAMIC PROGRAMMING

O(n × m) time

O(n × m) space

Each cell in the DP table is computed exactly once from previously solved subproblems. The table dimensions determine both time and space. Look for the state variables — each unique combination of state values is one cell. Often a rolling array can reduce space by one dimension.

Shortcut: Count your DP state dimensions → that’s your time. Can you drop one? That’s your space optimization.

Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Overflow in intermediate arithmetic

Wrong move: Temporary multiplications exceed integer bounds.

Usually fails on: Large inputs wrap around unexpectedly.

Fix: Use wider types, modular arithmetic, or rearranged operations.

State misses one required dimension

Wrong move: An incomplete state merges distinct subproblems and caches incorrect answers.

Usually fails on: Correctness breaks on cases that differ only in hidden state.

Fix: Define state so each unique subproblem maps to one DP cell.