http://codeforces.com/problemset/problem/218/B
This is a very easy problem to solve given that you know what data structure to use!
The data structure you need here is a heap. A heap is a tree like data structure which offers O(log(n)) inserts and removes and it also keeps the smallest or biggest element at the head.
Here is my code for solving the question:
PriorityQueue<> is the heap like data structure in java. It is a min-heap by default so I used some trickery to quickly convert it into a max-heap.
import java.util.*; public class B { public static void main(String[] args) { Scanner sc = new Scanner(System.in); int n = sc.nextInt(); int m = sc.nextInt(); int[] seats = new int[m]; for (int i = 0; i < seats.length; i++) { seats[i] = sc.nextInt(); } sc.close(); PriorityQueue<Integer> maxHeap = new PriorityQueue<Integer>(); PriorityQueue<Integer> minHeap = new PriorityQueue<Integer>(); for (int i = 0; i < seats.length; i++) { if (seats[i] != 0) { maxHeap.add(-seats[i]); minHeap.add(seats[i]); } } long max = 0; for (int i = 0; i < n; i++) { int t = -maxHeap.poll(); max += t; if (t - 1 != 0) maxHeap.add(-(t - 1)); } long min = 0; for (int i = 0; i < n; i++) { int t = minHeap.poll(); min += t; if (t - 1 != 0) minHeap.add(t - 1); } System.out.println(max + " " + min); } }
Thanks bro! You saved my life, it’s true, this problem is very easy after you know that you can solve it using a priority queue.