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:**

Input:coins =`[1, 2, 5]`

, amount =`11`

Output:`3`

Explanation:11 = 5 + 5 + 1

**Example 2:**

Input:coins =`[2]`

, amount =`3`

Output:-1

**Note**:

You may assume that you have an infinite number of each kind of coin.

## Solution : Dynamic Programming

**Top Down Approach : Recursion + Memoization**

class Solution { public int coinChange(int[] coins, int amount) { //Base case if(amount == 0) return 0; int[] dp = new int[amount+1]; int res = minCoins(amount,coins,coins.length,dp); return res == Integer.MAX_VALUE ? -1 : res; } public int minCoins(int n,int[] coins,int T,int[] dp) { //Base case if(n == 0) return 0; //Lookup if(dp[n] != 0) return dp[n]; //Recursive Case int ans = Integer.MAX_VALUE; for(int i=0;i<T;i++) { if(n-coins[i] >= 0) { int subProblem = minCoins(n-coins[i],coins,T,dp); if(subProblem != Integer.MAX_VALUE) ans = Math.min(ans,subProblem + 1); } } dp[n] = ans; return dp[n]; } }

**Time Complexity: O(T * N)**

**Space Complexity: O(N)**

## Bottom Up Approach

class Solution { public int coinChange(int[] coins, int amount) { if(amount == 0) return 0; int res = findMinCoinsBU(amount,coins,coins.length); return res == Integer.MAX_VALUE ? -1 : res; } public int findMinCoinsBU(int N,int[] coins,int T) { int[] dp = new int[N+1]; for(int n=1;n<=N;n++) { dp[n] = Integer.MAX_VALUE; for(int i=0;i<T;i++) { if(n - coins[i] >= 0) { int subProblem = dp[n-coins[i]]; if(subProblem != Integer.MAX_VALUE) dp[n] = Math.min(subProblem+1, dp[n]); } } } return dp[N]; } }

**Time Complexity: O(T * N)**

**Space Complexity: O(N)**