Learning Lab · Maintained demo

Binary Heap Explorer

Coordinate a complete-binary-tree view with its array representation while inserting, extracting, deleting, updating, and heapifying values.

Insert

Extract root

Delete

Update key

Build from array

Heap tree representation

Array representation

Operation explanation

Concept reference

Binary heap

A complete binary tree whose parent is always ordered before its children. A min heap keeps the smallest key at the root; a max heap keeps the largest.

Defining rules

  • Every level is full except possibly the last.
  • The last level fills from left to right.
  • Parent index is ⌊(i − 1) / 2⌋; children are 2i + 1 and 2i + 2.

Complexity

Peek is O(1). Insert, extract, update, and delete are O(log n). Building a heap bottom-up is O(n).

Tradeoffs & mistakes

Heaps provide fast access only to the root, not ordered traversal. Common errors include breaking completeness or restoring order in the wrong direction.

Indices begin at 0. Changing heap type rebuilds the ordering rule for the existing values.