Example: FindKthElementHeap in Java

// FindKthElementHeap
import java.util.PriorityQueue;
import java.util.Collections; // For reverse order comparator

public class Main {
    public static void main(String[] args) {
        int[] arr = {7, 10, 4, 3, 20, 15};
        int k = 3;

        System.out.println("Original Array: " + Arrays.toString(arr));

        // Find Kth Smallest Element using a Max-Heap
        // A max-heap stores the 'k' largest elements seen so far.
        // The root will be the largest among these 'k', if current element < root, replace.
        PriorityQueue<Integer> maxHeap = new PriorityQueue<>(Collections.reverseOrder());
        for (int num : arr) {
            maxHeap.offer(num); // Add element
            if (maxHeap.size() > k) {
                maxHeap.poll(); // Remove the largest element if size exceeds k
            }
        }
        // Step 1: Iterate through the array.
        // Step 2: Add each element to a max-heap.
        // Step 3: If heap size exceeds k, remove the largest element (heap's root).
        // Step 4: The root of the max-heap after iteration will be the k-th smallest.
        System.out.println(k + "th Smallest Element (via Max-Heap): " + maxHeap.peek());


        // Find Kth Largest Element using a Min-Heap
        // A min-heap stores the 'k' smallest elements seen so far.
        // The root will be the smallest among these 'k', if current element > root, replace.
        PriorityQueue<Integer> minHeap = new PriorityQueue<>(); // Default is min-heap
        for (int num : arr) {
            minHeap.offer(num); // Add element
            if (minHeap.size() > k) {
                minHeap.poll(); // Remove the smallest element if size exceeds k
            }
        }
        // Step 1: Iterate through the array.
        // Step 2: Add each element to a min-heap.
        // Step 3: If heap size exceeds k, remove the smallest element (heap's root).
        // Step 4: The root of the min-heap after iteration will be the k-th largest.
        System.out.println(k + "th Largest Element (via Min-Heap): " + minHeap.peek());
    }
}