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.
Break down a hard problem into reliable checkpoints, edge-case handling, and complexity trade-offs.
You are given two integers n and maxValue, which are used to describe an ideal array.
A 0-indexed integer array arr of length n is considered ideal if the following conditions hold:
arr[i] is a value from 1 to maxValue, for 0 <= i < n.arr[i] is divisible by arr[i - 1], for 0 < i < n.Return the number of distinct ideal arrays of length n. Since the answer may be very large, return it modulo 109 + 7.
Example 1:
Input: n = 2, maxValue = 5 Output: 10 Explanation: The following are the possible ideal arrays: - Arrays starting with the value 1 (5 arrays): [1,1], [1,2], [1,3], [1,4], [1,5] - Arrays starting with the value 2 (2 arrays): [2,2], [2,4] - Arrays starting with the value 3 (1 array): [3,3] - Arrays starting with the value 4 (1 array): [4,4] - Arrays starting with the value 5 (1 array): [5,5] There are a total of 5 + 2 + 1 + 1 + 1 = 10 distinct ideal arrays.
Example 2:
Input: n = 5, maxValue = 3 Output: 11 Explanation: The following are the possible ideal arrays: - Arrays starting with the value 1 (9 arrays): - With no other distinct values (1 array): [1,1,1,1,1] - With 2nd distinct value 2 (4 arrays): [1,1,1,1,2], [1,1,1,2,2], [1,1,2,2,2], [1,2,2,2,2] - With 2nd distinct value 3 (4 arrays): [1,1,1,1,3], [1,1,1,3,3], [1,1,3,3,3], [1,3,3,3,3] - Arrays starting with the value 2 (1 array): [2,2,2,2,2] - Arrays starting with the value 3 (1 array): [3,3,3,3,3] There are a total of 9 + 1 + 1 = 11 distinct ideal arrays.
Constraints:
2 <= n <= 1041 <= maxValue <= 104Problem summary: You are given two integers n and maxValue, which are used to describe an ideal array. A 0-indexed integer array arr of length n is considered ideal if the following conditions hold: Every arr[i] is a value from 1 to maxValue, for 0 <= i < n. Every arr[i] is divisible by arr[i - 1], for 0 < i < n. Return the number of distinct ideal arrays of length n. Since the answer may be very large, return it modulo 109 + 7.
Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.
Pattern signal: Math · Dynamic Programming
2 5
5 3
count-ways-to-make-array-with-product)count-the-number-of-beautiful-subarrays)Source-backed implementations are provided below for direct study and interview prep.
// Accepted solution for LeetCode #2338: Count the Number of Ideal Arrays
class Solution {
public int idealArrays(int n, int maxValue) {
final int mod = (int) 1e9 + 7;
int[][] c = new int[n][16];
for (int i = 0; i < n; ++i) {
for (int j = 0; j <= i && j < 16; ++j) {
c[i][j] = j == 0 ? 1 : (c[i - 1][j] + c[i - 1][j - 1]) % mod;
}
}
long[][] f = new long[maxValue + 1][16];
for (int i = 1; i <= maxValue; ++i) {
f[i][1] = 1;
}
for (int j = 1; j < 15; ++j) {
for (int i = 1; i <= maxValue; ++i) {
int k = 2;
for (; k * i <= maxValue; ++k) {
f[k * i][j + 1] = (f[k * i][j + 1] + f[i][j]) % mod;
}
}
}
long ans = 0;
for (int i = 1; i <= maxValue; ++i) {
for (int j = 1; j < 16; ++j) {
ans = (ans + f[i][j] * c[n - 1][j - 1]) % mod;
}
}
return (int) ans;
}
}
// Accepted solution for LeetCode #2338: Count the Number of Ideal Arrays
func idealArrays(n int, maxValue int) (ans int) {
const mod = int(1e9 + 7)
c := make([][]int, n)
for i := 0; i < n; i++ {
c[i] = make([]int, 16)
for j := 0; j <= i && j < 16; j++ {
if j == 0 {
c[i][j] = 1
} else {
c[i][j] = (c[i-1][j] + c[i-1][j-1]) % mod
}
}
}
f := make([][16]int, maxValue+1)
for i := 1; i <= maxValue; i++ {
f[i][1] = 1
}
for j := 1; j < 15; j++ {
for i := 1; i <= maxValue; i++ {
for k := 2; k*i <= maxValue; k++ {
f[k*i][j+1] = (f[k*i][j+1] + f[i][j]) % mod
}
}
}
for i := 1; i <= maxValue; i++ {
for j := 1; j < 16; j++ {
ans = (ans + f[i][j]*c[n-1][j-1]) % mod
}
}
return
}
# Accepted solution for LeetCode #2338: Count the Number of Ideal Arrays
class Solution:
def idealArrays(self, n: int, maxValue: int) -> int:
c = [[0] * 16 for _ in range(n)]
mod = 10**9 + 7
for i in range(n):
for j in range(min(16, i + 1)):
c[i][j] = 1 if j == 0 else (c[i - 1][j] + c[i - 1][j - 1]) % mod
f = [[0] * 16 for _ in range(maxValue + 1)]
for i in range(1, maxValue + 1):
f[i][1] = 1
for j in range(1, 15):
for i in range(1, maxValue + 1):
k = 2
while k * i <= maxValue:
f[k * i][j + 1] = (f[k * i][j + 1] + f[i][j]) % mod
k += 1
ans = 0
for i in range(1, maxValue + 1):
for j in range(1, 16):
ans = (ans + f[i][j] * c[-1][j - 1]) % mod
return ans
// Accepted solution for LeetCode #2338: Count the Number of Ideal Arrays
/**
* [2338] Count the Number of Ideal Arrays
*
* You are given two integers n and maxValue, which are used to describe an ideal array.
* A 0-indexed integer array arr of length n is considered ideal if the following conditions hold:
*
* Every arr[i] is a value from 1 to maxValue, for 0 <= i < n.
* Every arr[i] is divisible by arr[i - 1], for 0 < i < n.
*
* Return the number of distinct ideal arrays of length n. Since the answer may be very large, return it modulo 10^9 + 7.
*
* Example 1:
*
* Input: n = 2, maxValue = 5
* Output: 10
* Explanation: The following are the possible ideal arrays:
* - Arrays starting with the value 1 (5 arrays): [1,1], [1,2], [1,3], [1,4], [1,5]
* - Arrays starting with the value 2 (2 arrays): [2,2], [2,4]
* - Arrays starting with the value 3 (1 array): [3,3]
* - Arrays starting with the value 4 (1 array): [4,4]
* - Arrays starting with the value 5 (1 array): [5,5]
* There are a total of 5 + 2 + 1 + 1 + 1 = 10 distinct ideal arrays.
*
* Example 2:
*
* Input: n = 5, maxValue = 3
* Output: 11
* Explanation: The following are the possible ideal arrays:
* - Arrays starting with the value 1 (9 arrays):
* - With no other distinct values (1 array): [1,1,1,1,1]
* - With 2^nd distinct value 2 (4 arrays): [1,1,1,1,2], [1,1,1,2,2], [1,1,2,2,2], [1,2,2,2,2]
* - With 2^nd distinct value 3 (4 arrays): [1,1,1,1,3], [1,1,1,3,3], [1,1,3,3,3], [1,3,3,3,3]
* - Arrays starting with the value 2 (1 array): [2,2,2,2,2]
* - Arrays starting with the value 3 (1 array): [3,3,3,3,3]
* There are a total of 9 + 1 + 1 = 11 distinct ideal arrays.
*
*
* Constraints:
*
* 2 <= n <= 10^4
* 1 <= maxValue <= 10^4
*
*/
pub struct Solution {}
// problem: https://leetcode.com/problems/count-the-number-of-ideal-arrays/
// discuss: https://leetcode.com/problems/count-the-number-of-ideal-arrays/discuss/?currentPage=1&orderBy=most_votes&query=
// submission codes start here
impl Solution {
pub fn ideal_arrays(n: i32, max_value: i32) -> i32 {
0
}
}
// submission codes end
#[cfg(test)]
mod tests {
use super::*;
#[test]
#[ignore]
fn test_2338_example_1() {
let n = 2;
let max_value = 5;
let result = 10;
assert_eq!(Solution::ideal_arrays(n, max_value), result);
}
#[test]
#[ignore]
fn test_2338_example_2() {
let n = 5;
let max_value = 3;
let result = 11;
assert_eq!(Solution::ideal_arrays(n, max_value), result);
}
}
// Accepted solution for LeetCode #2338: Count the Number of Ideal Arrays
function idealArrays(n: number, maxValue: number): number {
const mod = 1e9 + 7;
const c: number[][] = Array.from({ length: n }, () => Array(16).fill(0));
for (let i = 0; i < n; i++) {
for (let j = 0; j <= i && j < 16; j++) {
if (j === 0) {
c[i][j] = 1;
} else {
c[i][j] = (c[i - 1][j] + c[i - 1][j - 1]) % mod;
}
}
}
const f: number[][] = Array.from({ length: maxValue + 1 }, () => Array(16).fill(0));
for (let i = 1; i <= maxValue; i++) {
f[i][1] = 1;
}
for (let j = 1; j < 15; j++) {
for (let i = 1; i <= maxValue; i++) {
for (let k = 2; k * i <= maxValue; k++) {
f[k * i][j + 1] = (f[k * i][j + 1] + f[i][j]) % mod;
}
}
}
let ans = 0;
for (let i = 1; i <= maxValue; i++) {
for (let j = 1; j < 16; j++) {
ans = (ans + f[i][j] * c[n - 1][j - 1]) % mod;
}
}
return ans;
}
Use this to step through a reusable interview workflow for this problem.
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.
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.
Review these before coding to avoid predictable interview regressions.
Wrong move: Temporary multiplications exceed integer bounds.
Usually fails on: Large inputs wrap around unexpectedly.
Fix: Use wider types, modular arithmetic, or rearranged operations.
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.