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Update EggDropping.java
## Changes Made 1. Improved Documentation - Added comprehensive class-level JavaDoc - Added detailed method documentation with @param and @return tags - Added time and space complexity analysis (O(n*m*m) time, O(n*m) space) - Added comments explaining DP state transitions and base cases 2. Code Quality Improvements - Made class final and constructor private (utility class best practice) - Added try-catch block in main method for better error handling The core dynamic programming algorithm remains unchanged, maintaining its educational value while improving code quality and documentation.
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package com.thealgorithms.dynamicprogramming;
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/**
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* DynamicProgramming solution for the Egg Dropping Puzzle
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* Dynamic Programming solution for the Egg Dropping Puzzle
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* The problem is to find the minimum number of attempts needed in the worst case to find the critical
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* floor from which if an egg is dropped, it will break.
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* Time Complexity: O(n * m * m), where n is number of eggs and m is number of floors
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* Space Complexity: O(n * m) to store the DP table
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*/
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public final class EggDropping {
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private EggDropping() {
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// private constructor to prevent instantiation
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}
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// min trials with n eggs and m floors
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public static int minTrials(int n, int m) {
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int[][] eggFloor = new int[n + 1][m + 1];
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int result;
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int x;
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for (int i = 1; i <= n; i++) {
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eggFloor[i][0] = 0; // Zero trial for zero floor.
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eggFloor[i][1] = 1; // One trial for one floor
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/**
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* Finds minimum number of trials needed in worst case for n eggs and m floors
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*
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* @param eggs The number of eggs available
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* @param floors The number of floors in the building
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* @return Minimum number of trials needed in worst case
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* @throws IllegalArgumentException if eggs <= 0 or floors < 0
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*/
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public static int minTrials(int eggs, int floors) {
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if (eggs <= 0 || floors < 0) {
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throw new IllegalArgumentException("Number of eggs must be positive and floors must be non-negative");
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}
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// j trials for only 1 egg
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for (int j = 1; j <= m; j++) {
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eggFloor[1][j] = j;
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// dp[i][j] represents minimum number of trials needed for i eggs and j floors
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int[][] dp = new int[eggs + 1][floors + 1];
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// Base case 1: Zero trials for zero floor
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// Base case 2: One trial for one floor
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for (int i = 1; i <= eggs; i++) {
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dp[i][0] = 0;
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dp[i][1] = 1;
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}
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// Using bottom-up approach in DP
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for (int i = 2; i <= n; i++) {
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for (int j = 2; j <= m; j++) {
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eggFloor[i][j] = Integer.MAX_VALUE;
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for (x = 1; x <= j; x++) {
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result = 1 + Math.max(eggFloor[i - 1][x - 1], eggFloor[i][j - x]);
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// choose min of all values for particular x
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if (result < eggFloor[i][j]) {
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eggFloor[i][j] = result;
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}
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// Base case 3: With one egg, need to try every floor from bottom
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for (int j = 1; j <= floors; j++) {
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dp[1][j] = j;
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}
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// Fill rest of the entries in table using optimal substructure property
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for (int i = 2; i <= eggs; i++) {
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for (int j = 2; j <= floors; j++) {
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dp[i][j] = Integer.MAX_VALUE;
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// Try dropping egg from each floor and find minimum trials needed
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for (int k = 1; k <= j; k++) {
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// Maximum of:
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// 1) Egg breaks at floor k: Check below floors with i-1 eggs
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// 2) Egg doesn't break: Check above floors with i eggs
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int attempts = 1 + Math.max(dp[i - 1][k - 1], dp[i][j - k]);
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dp[i][j] = Math.min(dp[i][j], attempts);
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}
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}
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}
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return eggFloor[n][m];
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return dp[eggs][floors];
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}
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/**
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* Example usage
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*/
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public static void main(String[] args) {
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int n = 2;
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int m = 4;
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// result outputs min no. of trials in worst case for n eggs and m floors
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int result = minTrials(n, m);
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System.out.println(result);
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try {
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// Example: 2 eggs and 4 floors
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System.out.println("Minimum number of trials in worst case with 2 eggs and 4 floors: "
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+ minTrials(2, 4));
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// Additional test case
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System.out.println("Minimum number of trials in worst case with 3 eggs and 5 floors: "
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+ minTrials(3, 5));
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} catch (IllegalArgumentException e) {
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System.err.println("Error: " + e.getMessage());
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}
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}
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}

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