Heap

Introduction:

In computer science, the heap data structure plays a vital role in organizing and managing data efficiently. It is a specialized tree-based data structure that satisfies the heap property. A heap is an almost complete tree where the key of each parent node is either greater than or equal to (in a max heap) or less than or equal to (in a min heap) the key of its children. The topmost node, known as the root node, has no parents. Let’s explore the heap data structure further and learn how to implement it in different programming languages.

Understanding Heap Data Structure:

The heap data structure is commonly used to implement priority queues and heapsort algorithms. It provides efficient operations for inserting, deleting, and finding the maximum or minimum element, depending on the type of heap.

There are two types of heaps:

Max Heap: In a max heap, the key of each parent node is greater than or equal to the keys of its children. The maximum element is always at the root.
Min Heap: In a min heap, the key of each parent node is less than or equal to the keys of its children. The minimum element is always at the root.

Links

Code Examples

JavaScript
class MaxHeap {
  constructor() {
    this.heap = [];
  }

  insert(value) {
    this.heap.push(value);
    let currentIndex = this.heap.length - 1;

    while (currentIndex > 0) {
      const parentIndex = Math.floor((currentIndex - 1) / 2);

      if (this.heap[currentIndex] > this.heap[parentIndex]) {
        [this.heap[currentIndex], this.heap[parentIndex]] = [
          this.heap[parentIndex],
          this.heap[currentIndex],
        ];
      } else {
        break;
      }

      currentIndex = parentIndex;
    }
  }

  // Other heap operations (delete, get maximum, etc.) can be implemented similarly
}

Python
class MaxHeap:
    def __init__(self):
        self.heap = []

    def insert(self, value):
        self.heap.append(value)
        current_index = len(self.heap) - 1

        while current_index > 0:
            parent_index = (current_index - 1) // 2

            if self.heap[current_index] > self.heap[parent_index]:
                self.heap[current_index], self.heap[parent_index] = self.heap[parent_index], self.heap[current_index]
            else:
                break

            current_index = parent_index

    # Other heap operations (delete, get maximum, etc.) can be implemented similarly

PHP
class MaxHeap {
    private $heap = [];

    public function insert($value) {
        array_push($this->heap, $value);
        $current_index = count($this->heap) - 1;

        while ($current_index > 0) {
            $parent_index = (int)(($current_index - 1) / 2);

            if ($this->heap[$current_index] > $this->heap[$parent_index]) {
                [$this->heap[$current_index], $this->heap[$parent_index]] = [$this->heap[$parent_index], $this->heap[$current_index]];
            } else {
                break;
            }

            $current_index = $parent_index;
        }
    }

    // Other heap operations (delete, get maximum, etc.) can be implemented similarly
}

Conclusion