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.
Move from brute-force thinking to an efficient approach using math strategy.
You are given two identical eggs and you have access to a building with n floors labeled from 1 to n.
You know that there exists a floor f where 0 <= f <= n such that any egg dropped at a floor higher than f will break, and any egg dropped at or below floor f will not break.
In each move, you may take an unbroken egg and drop it from any floor x (where 1 <= x <= n). If the egg breaks, you can no longer use it. However, if the egg does not break, you may reuse it in future moves.
Return the minimum number of moves that you need to determine with certainty what the value of f is.
Example 1:
Input: n = 2 Output: 2 Explanation: We can drop the first egg from floor 1 and the second egg from floor 2. If the first egg breaks, we know that f = 0. If the second egg breaks but the first egg didn't, we know that f = 1. Otherwise, if both eggs survive, we know that f = 2.
Example 2:
Input: n = 100 Output: 14 Explanation: One optimal strategy is: - Drop the 1st egg at floor 9. If it breaks, we know f is between 0 and 8. Drop the 2nd egg starting from floor 1 and going up one at a time to find f within 8 more drops. Total drops is 1 + 8 = 9. - If the 1st egg does not break, drop the 1st egg again at floor 22. If it breaks, we know f is between 9 and 21. Drop the 2nd egg starting from floor 10 and going up one at a time to find f within 12 more drops. Total drops is 2 + 12 = 14. - If the 1st egg does not break again, follow a similar process dropping the 1st egg from floors 34, 45, 55, 64, 72, 79, 85, 90, 94, 97, 99, and 100. Regardless of the outcome, it takes at most 14 drops to determine f.
Constraints:
1 <= n <= 1000Problem summary: You are given two identical eggs and you have access to a building with n floors labeled from 1 to n. You know that there exists a floor f where 0 <= f <= n such that any egg dropped at a floor higher than f will break, and any egg dropped at or below floor f will not break. In each move, you may take an unbroken egg and drop it from any floor x (where 1 <= x <= n). If the egg breaks, you can no longer use it. However, if the egg does not break, you may reuse it in future moves. Return the minimum number of moves that you need to determine with certainty what the value of f is.
Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.
Pattern signal: Math · Dynamic Programming
2
100
super-egg-drop)Source-backed implementations are provided below for direct study and interview prep.
// Accepted solution for LeetCode #1884: Egg Drop With 2 Eggs and N Floors
class Solution {
public int twoEggDrop(int n) {
int[] f = new int[n + 1];
Arrays.fill(f, 1 << 29);
f[0] = 0;
for (int i = 1; i <= n; i++) {
for (int j = 1; j <= i; j++) {
f[i] = Math.min(f[i], 1 + Math.max(j - 1, f[i - j]));
}
}
return f[n];
}
}
// Accepted solution for LeetCode #1884: Egg Drop With 2 Eggs and N Floors
func twoEggDrop(n int) int {
f := make([]int, n+1)
for i := range f {
f[i] = 1 << 29
}
f[0] = 0
for i := 1; i <= n; i++ {
for j := 1; j <= i; j++ {
f[i] = min(f[i], 1+max(j-1, f[i-j]))
}
}
return f[n]
}
# Accepted solution for LeetCode #1884: Egg Drop With 2 Eggs and N Floors
class Solution:
def twoEggDrop(self, n: int) -> int:
f = [0] + [inf] * n
for i in range(1, n + 1):
for j in range(1, i + 1):
f[i] = min(f[i], 1 + max(j - 1, f[i - j]))
return f[n]
// Accepted solution for LeetCode #1884: Egg Drop With 2 Eggs and N Floors
/**
* [1884] Egg Drop With 2 Eggs and N Floors
*
* You are given two identical eggs and you have access to a building with n floors labeled from 1 to n.
* You know that there exists a floor f where 0 <= f <= n such that any egg dropped at a floor higher than f will break, and any egg dropped at or below floor f will not break.
* In each move, you may take an unbroken egg and drop it from any floor x (where 1 <= x <= n). If the egg breaks, you can no longer use it. However, if the egg does not break, you may reuse it in future moves.
* Return the minimum number of moves that you need to determine with certainty what the value of f is.
*
* Example 1:
*
* Input: n = 2
* Output: 2
* Explanation: We can drop the first egg from floor 1 and the second egg from floor 2.
* If the first egg breaks, we know that f = 0.
* If the second egg breaks but the first egg didn't, we know that f = 1.
* Otherwise, if both eggs survive, we know that f = 2.
*
* Example 2:
*
* Input: n = 100
* Output: 14
* Explanation: One optimal strategy is:
* - Drop the 1st egg at floor 9. If it breaks, we know f is between 0 and 8. Drop the 2nd egg starting from floor 1 and going up one at a time to find f within 8 more drops. Total drops is 1 + 8 = 9.
* - If the 1st egg does not break, drop the 1st egg again at floor 22. If it breaks, we know f is between 9 and 21. Drop the 2nd egg starting from floor 10 and going up one at a time to find f within 12 more drops. Total drops is 2 + 12 = 14.
* - If the 1st egg does not break again, follow a similar process dropping the 1st egg from floors 34, 45, 55, 64, 72, 79, 85, 90, 94, 97, 99, and 100.
* Regardless of the outcome, it takes at most 14 drops to determine f.
*
*
* Constraints:
*
* 1 <= n <= 1000
*
*/
pub struct Solution {}
// problem: https://leetcode.com/problems/egg-drop-with-2-eggs-and-n-floors/
// discuss: https://leetcode.com/problems/egg-drop-with-2-eggs-and-n-floors/discuss/?currentPage=1&orderBy=most_votes&query=
// submission codes start here
impl Solution {
pub fn two_egg_drop(n: i32) -> i32 {
(((-1.0 + (1.0 + 8.0 * (n as f64)).sqrt()) / 2.0).ceil()) as i32
}
}
// submission codes end
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_1884_example_1() {
let n = 2;
let result = 2;
assert_eq!(Solution::two_egg_drop(n), result);
}
#[test]
fn test_1884_example_2() {
let n = 100;
let result = 14;
assert_eq!(Solution::two_egg_drop(n), result);
}
}
// Accepted solution for LeetCode #1884: Egg Drop With 2 Eggs and N Floors
function twoEggDrop(n: number): number {
const f: number[] = Array(n + 1).fill(Infinity);
f[0] = 0;
for (let i = 1; i <= n; ++i) {
for (let j = 1; j <= i; ++j) {
f[i] = Math.min(f[i], 1 + Math.max(j - 1, f[i - j]));
}
}
return f[n];
}
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.