coinChange.cpp

// Source : https://leetcode.com/problems/coin-change/
// Author : Calinescu Valentin, Hao Chen
// Date   : 2015-12-28

/*************************************************************************************** 
 *
 * You are given coins of different denominations and a total amount of money amount. 
 * Write a function to compute the fewest number of coins that you need to make up that
 * amount. If that amount of money cannot be made up by any combination of the coins,
 * return -1.
 * 
 * Example 1:
 * coins = [1, 2, 5], amount = 11
 * return 3 (11 = 5 + 5 + 1)
 * 
 * Example 2:
 * coins = [2], amount = 3
 * return -1.
 * 
 * Note:
 * You may assume that you have an infinite number of each kind of coin.
 * 
 * Credits:
 * Special thanks to @jianchao.li.fighter for adding this problem and creating all test 
 * cases.
 * 
 ***************************************************************************************/


/* Recursive solution - TIME LIMIT ERROR */
class Solution {
public:
    int coinChange(vector<int>& coins, int amount) {  
        int result = INT_MAX;
        if ( amount == 0 ) return 0;
        if ( amount < 0 ) return -1;
        for (int i=0; i<coins.size(); i++) {
            if ( amount - coins[i] < 0 ) continue;
            int r = coinChange(coins, amount - coins[i]);
            if ( r == -1 ) continue;
            if (result > r )  result = r + 1;
        }
        return result == INT_MAX ? -1 : result;
    }
}


 /* 
 * Solution 1 - O(N * amount)
 * =========
 *
 * This problem can be solved using dynamic programming, thus building the optimal
 * solution from previous smaller ones. For every coin of value t and every sum of money
 * i the sum can be traced back to a previous sum i - t that was already computed and uses
 * the smallest number of coins possible. This way we can construct every sum i as the
 * minimum of all these previous sums for every coin value. To be sure we'll find a minimum
 * we can populate the solution vector with an amount bigger than the maximum possible, 
 * which is amount + 1(when the sum is made up of only coins of value 1). The only exception
 * is sol[0] which is 0 as we need 0 coins to have a sum of 0. In the end we need to look
 * if the program found a solution in sol[amount] or it remained the same, in which case we
 * can return -1.
 * 
 */
class Solution {
public:
    
    int coinChange(vector<int>& coins, int amount) {
        int sol[amount + 1];
        sol[0] = 0;
        for(int i = 1; i <= amount; i++)
            sol[i] = amount + 1;
        for(int i = 0; i < coins.size(); i++)
        {
            for(int j = coins[i]; j <= amount; j++)
                sol[j] = min(sol[j], sol[j - coins[i]] + 1);
        }
        if(sol[amount] != amount + 1)
            return sol[amount];
        else
            return -1;
    }
};


//Another DP implmentation, same idea above 
class Solution {
public:
    int coinChange(vector<int>& coins, int amount) {
        const int MAX = amount +1;
        vector<int> dp(amount+1, MAX);
        dp[0]=0;
        
        for(int i=1; i<=amount; i++) {
            for (int j=0; j<coins.size(); j++){
                if (i >= coins[j]) {
                    dp[i] = min( dp[i], dp[i-coins[j]] + 1 );
                }
            }
        }

        return dp[amount]==MAX ? -1 : dp[amount];
    }
};