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Misha And Candies

Logical Breakdown

  • [ ] Subproblem Identification:
  • [ ] Optimal Substructure:
  • [ ] Constraint Handling: (e.g., Modulo \(10^9 + 7\))
  • [ ] Optimization: (Matrix Exponentiation if 'A' is huge)

Mathematical Rigor

State Definition

Let \(dp[i]\) be the state for the \(i\)-th subproblem.

Recurrence Relation

\[ dp[i] = ... \]

Visualization

graph TD A["Current State"] --> B["Previous State 1"] A --> C["Previous State 2"]

Complexity Analysis

Approach Time Complexity Space Complexity
Iterative DP \(O(N)\) \(O(1)\)

Code Reference

package com.dsa.heaps;

/ * ============================================================================================ * PROBLEM: Misha and Candies * ============================================================================================ * * --------------------- * 1. Problem Description * --------------------- * Misha has N boxes of candies. In each step: * 1. Pick the box with the minimum number of candies (must be <= B). * 2. Eat floor(minCandies / 2) candies. * 3. Add the remaining candies (minCandies - eaten) to the next minimum box. * 4. Remove the original box from consideration. * Task: Calculate total candies eaten until no box with <= B candies remains. * * --------------------- * 2. Logical Breakdown & Mathematical Formulation * --------------------- * This problem is a simulation of a greedy process using a Min-Heap. * * Algorithm: * 1. Initialization: * - Insert all candy counts from the boxes into a Min-Priority Queue. * * 2. Iterative Consumption: * While the Min-Heap is not empty: * a. Extract the minimum box minBox. * b. If minBox > B, stop the process (Misha won't eat from this box). * c. Calculate eaten: \(eaten = \lfloor minBox / 2 \rfloor\). * d. Add eaten to totalEaten. * e. Calculate remaining: \(rem = minBox - eaten\). * f. If the heap is not empty: * - Extract the next minimum box nextMin. * - Add rem to nextMin. * - If the updated nextMin <= B, push it back into the heap. * (If > B, it remains out of the heap as Misha won't pick it anymore). * * --------------------- * 3. Constraints & Complexity Analysis * --------------------- * Time Complexity: * O(N log N) * - Initial heap construction: O(N log N). * - Each box is extracted once: O(N log N). * * Space Complexity: * O(N) to store the candy counts in the Priority Queue. * ============================================================================================ */ public class MishaAndCandies { public int solve(int[] a1, int A) { // TODO: Implement solution return 0; } }