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# Min Cost Climbing Stairs

ID: 746; easy

## Solution 1

class Solution {
public int minCostClimbingStairs(int[] cost) {
int[] minCost = new int[cost.length + 1];
for (int i = 2; i < minCost.length; i++) {
int oneStep = minCost[i - 1] + cost[i - 1];
int twoStep = minCost[i - 2] + cost[i - 2];
minCost[i] = Math.min(oneStep, twoStep);
}
return minCost[minCost.length - 1];
}
}
This is the DP equation:
$minCost[i] = min(minCost[i-1] + cost[i-1], minCost[i-2], cost[i-2])$
For the minimum cost to reach the ith step, we either came from the one-step hop or from the two-step hop (with their corresponding minimum costs as well).
Time complexity: O(n)
Space complexity: O(n)

## Solution 2

class Solution {
public int minCostClimbingStairs(int[] cost) {
int downOne = 0;
int downTwo = 0;
for (int i = 2; i < cost.length + 1; i++) {
int oneStep = downOne + cost[i - 1];
int twoStep = downTwo + cost[i - 2];
int tempDownTwo = downOne;
downOne = Math.min(oneStep, twoStep);
downTwo = tempDownTwo;
}
return downOne;
}
}
Similarly, we can improve the space complexity by just using variables instead of the whole array. It become a little more abstract now.
downOne and downTwo represents the minimum cost to reach one step and two steps below the current step that we are taking. Inside the loop, each iteration, downOne is after downTwo. We calculate the minimum and update downOne. Then, downTwo is updated to be the old downOne.