# Eggs dropping puzzle (Binomial Coefficient and Binary Search Solution)

• Difficulty Level : Expert
• Last Updated : 05 Aug, 2022

Given n eggs and k floors, find the minimum number of trials needed in worst case to find the floor below which all floors are safe. A floor is safe if dropping an egg from it does not break the egg. Please see n eggs and k floors. for complete statements

Example

```Input : n = 2, k = 10
Output : 4
We first try from 4-th floor. Two cases arise,
(1) If egg breaks, we have one egg left so we
need three more trials.
(2) If egg does not break, we try next from 7-th
floor. Again two cases arise.
We can notice that if we choose 4th floor as first
floor, 7-th as next floor and 9 as next of next floor,
we never exceed more than 4 trials.

Input : n = 2. k = 100
Output : 14```

We have discussed the problem for 2 eggs and k floors. We have also discussed a dynamic programming solution to find the solution. The dynamic programming solution is based on below recursive nature of the problem. Let us look at the discussed recursive formula from a different perspective.

How many floors we can cover with x trials?
When we drop an egg, two cases arise.

1. If egg breaks, then we are left with x-1 trials and n-1 eggs.
2. If egg does not break, then we are left with x-1 trials and n eggs
```Let maxFloors(x, n) be the maximum number of floors
that we can cover with x trials and n eggs. From above
two cases, we can write.

maxFloors(x, n) = maxFloors(x-1, n-1) + maxFloors(x-1, n) + 1
For all x >= 1 and n >= 1

Base cases :
We can't cover any floor with 0 trials or 0 eggs
maxFloors(0, n) = 0
maxFloors(x, 0) = 0

Since we need to cover k floors,
maxFloors(x, n) >= k           ----------(1)

The above recurrence simplifies to following,
Refer this for proof.

maxFloors(x, n) = &Sum;xCi
1 <= i <= n   ----------(2)
Here C represents Binomial Coefficient.

From above two equations, we can say.
&Sum;xCj  >= k
1 <= i <= n
Basically we need to find minimum value of x
that satisfies above inequality. We can find
such x using Binary Search.```

## C++

 `// C++ program to find minimum` `// number of trials in worst case.` `#include `   `using` `namespace` `std;`   `// Find sum of binomial coefficients xCi` `// (where i varies from 1 to n).` `int` `binomialCoeff(``int` `x, ``int` `n, ``int` `k)` `{` `    ``int` `sum = 0, term = 1;` `    ``for` `(``int` `i = 1; i <= n; ++i) {` `        ``term *= x - i + 1;` `        ``term /= i;` `        ``sum += term;` `        ``if` `(sum > k)` `            ``return` `sum;` `    ``}` `    ``return` `sum;` `}`   `// Do binary search to find minimum` `// number of trials in worst case.` `int` `minTrials(``int` `n, ``int` `k)` `{` `    ``// Initialize low and high as 1st` `    ``// and last floors` `    ``int` `low = 1, high = k;`   `    ``// Do binary search, for every mid,` `    ``// find sum of binomial coefficients and` `    ``// check if the sum is greater than k or not.` `    ``while` `(low <= high) {` `        ``int` `mid = (low + high) / 2;` `        ``if` `(binomialCoeff(mid, n, k) < k)` `            ``low = mid + 1;` `        ``else` `            ``high = mid;` `    ``}`   `    ``return` `low;` `}`   `/* Driver code*/` `int` `main()` `{` `    ``cout << minTrials(2, 10);` `    ``return` `0;` `}`

## Java

 `// Java program to find minimum` `// number of trials in worst case.` `class` `Geeks {`   `    ``// Find sum of binomial coefficients xCi` `    ``// (where i varies from 1 to n). If the sum` `    ``// becomes more than K` `    ``static` `int` `binomialCoeff(``int` `x, ``int` `n, ``int` `k)` `    ``{` `        ``int` `sum = ``0``, term = ``1``;` `        ``for` `(``int` `i = ``1``; i <= n && sum < k; ++i) {` `            ``term *= x - i + ``1``;` `            ``term /= i;` `            ``sum += term;` `        ``}` `        ``return` `sum;` `    ``}`   `    ``// Do binary search to find minimum` `    ``// number of trials in worst case.` `    ``static` `int` `minTrials(``int` `n, ``int` `k)` `    ``{` `        ``// Initialize low and high as 1st` `        ``// and last floors` `        ``int` `low = ``1``, high = k;`   `        ``// Do binary search, for every mid,` `        ``// find sum of binomial coefficients and` `        ``// check if the sum is greater than k or not.` `        ``while` `(low <= high) {` `            ``int` `mid = (low + high) / ``2``;` `            ``if` `(binomialCoeff(mid, n, k) < k)` `                ``low = mid + ``1``;` `            ``else` `                ``high = mid;` `        ``}`   `        ``return` `low;` `    ``}`   `    ``/* Driver code*/` `    ``public` `static` `void` `main(String args[])` `    ``{` `        ``System.out.println(minTrials(``2``, ``10``));` `    ``}` `}`   `// This code is contributed by ankita_saini`

## Python3

 `# Python3 program to find minimum` `# number of trials in worst case.`   `# Find sum of binomial coefficients` `# xCi (where i varies from 1 to n).` `# If the sum becomes more than K`     `def` `binomialCoeff(x, n, k):`   `    ``sum` `=` `0` `    ``term ``=` `1` `    ``i ``=` `1` `    ``while``(i <``=` `n ``and` `sum` `< k):` `        ``term ``*``=` `x ``-` `i ``+` `1` `        ``term ``/``=` `i` `        ``sum` `+``=` `term` `        ``i ``+``=` `1` `    ``return` `sum`   `# Do binary search to find minimum` `# number of trials in worst case.`     `def` `minTrials(n, k):`   `    ``# Initialize low and high as` `    ``# 1st and last floors` `    ``low ``=` `1` `    ``high ``=` `k`   `    ``# Do binary search, for every` `    ``# mid, find sum of binomial` `    ``# coefficients and check if` `    ``# the sum is greater than k or not.` `    ``while` `(low <``=` `high):`   `        ``mid ``=` `(low ``+` `high)``/``/``2` `        ``if` `(binomialCoeff(mid, n, k) < k):` `            ``low ``=` `mid ``+` `1` `        ``else``:` `            ``high ``=` `mid`   `    ``return` `low`     `# Driver Code` `print``(minTrials(``2``, ``10``))`   `# This code is contributed` `# by mits`

## Javascript

 `// C# program to find minimum` `// number of trials in worst case.` `using System;`   `class GFG {`   `    ``// Find sum of binomial coefficients` `    ``// xCi (where i varies from 1 to n).` `    ``// If the sum becomes more than K` `    ``static int binomialCoeff(int x, int n, int k)` `    ``{` `        ``int sum = 0, term = 1;` `        ``for` `(int i = 1; i <= n && sum < k; ++i) {` `            ``term *= x - i + 1;` `            ``term /= i;` `            ``sum += term;` `        ``}` `        ``return` `sum;` `    ``}`   `    ``// Do binary search to find minimum` `    ``// number of trials in worst case.` `    ``static int minTrials(int n, int k)` `    ``{` `        ``// Initialize low and high` `        ``// as 1st and last floors` `        ``int low = 1, high = k;`   `        ``// Do binary search, for every` `        ``// mid, find sum of binomial` `        ``// coefficients and check if the` `        ``// sum is greater than k or not.` `        ``while` `(low <= high) {` `            ``int mid = (low + high) / 2;` `            ``if` `(binomialCoeff(mid, n, k) < k)` `                ``low = mid + 1;` `            ``else` `                ``high = mid;` `        ``}`   `        ``return` `low;` `    ``}`   `    ``// Driver Code` `    ``public static void Main()` `    ``{` `        ``Console.WriteLine(minTrials(2, 10));` `    ``}` `}`   `// This code is contributed` `// by Akanksha Rai(Abby_akku)`

## PHP

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## Javascript

 ``

Output

`4`

Time Complexity : O(n Log k)

Another Approach:

The approach with O(n * k^2) has been discussed before, where dp[n][k] = 1 + max(dp[n – 1][i – 1], dp[n][k – i]) for i in 1…k. You checked all the possibilities in that approach.

Consider the problem in a different way:

```dp[m][x] means that, given x eggs and m moves,
what is the maximum number of floors that can be checked

The dp equation is: dp[m][x] = 1 + dp[m - 1][x - 1] + dp[m - 1][x],
which means we take 1 move to a floor.
If egg breaks, then we can check dp[m - 1][x - 1] floors.
If egg doesn't break, then we can check dp[m - 1][x] floors.```

## C++

 `// C++ program to find minimum number of trials in worst` `// case.` `#include ` `using` `namespace` `std;`   `int` `minTrials(``int` `n, ``int` `k)` `{` `    ``// Initialize 2D of size (k+1) * (n+1).` `    ``vector > dp(k + 1, vector<``int``>(n + 1, 0));` `    ``int` `m = 0; ``// Number of moves` `    ``while` `(dp[m][n] < k) {` `        ``m++;` `        ``for` `(``int` `x = 1; x <= n; x++) {` `            ``dp[m][x] = 1 + dp[m - 1][x - 1] + dp[m - 1][x];` `        ``}` `    ``}` `    ``return` `m;` `}`   `/* Driver code*/` `int` `main()` `{` `    ``cout << minTrials(2, 10);` `    ``return` `0;` `}`   `// This code is contributed by Arihant Jain (arihantjain01)`

Output

`4`

Optimization to one-dimensional DP

The above solution can be optimized to one-dimensional DP as follows:

## C++

 `// C++ program to find minimum number of trials in worst` `// case.` `#include ` `using` `namespace` `std;`   `int` `minTrials(``int` `n, ``int` `k)` `{` `    ``// Initialize array of size (n+1) and m as moves.` `    ``int` `dp[n + 1] = { 0 }, m;` `    ``for` `(m = 0; dp[n] < k; m++) {` `        ``for` `(``int` `x = n; x > 0; x--) {` `            ``dp[x] += 1 + dp[x - 1];` `        ``}` `    ``}` `    ``return` `m;` `}`   `/* Driver code*/` `int` `main()` `{` `    ``cout << minTrials(2, 10);` `    ``return` `0;` `}`   `// This code is contributed by Arihant Jain (arihantjain01)`

Output

`4`

Complexity Analysis:

• Time Complexity: O(n * log k)
• Auxiliary Space: O(n)

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