Binary Heap is a complete tree (All levels are completely filled except possibly the last level and the last level has all keys as left as possible). In other words, we can say that it’s an almost complete binary tree.

A Binary heap is typically represented as array. If we take a closer look, we can noticed that in a Heap with number of nodes n, the leaves start from a particular index and following it, all the nodes are leaves till index n.

Let’s see an example to observe this:

10 / \ 20 100 / 30

Let us represent this in the form of an array Arr whose index starts from 1 :

we have:

Arr[1] = 10

Arr[2] = 20

Arr[3] = 100

Arr[4] = 30

If we observe, the first leaf (i.e. 100) starts from the index 3. Following it Arr[4] is also a leaf.

By carefully analyzing, the following conclusion is observed:

The first leaf in a Heap starts from

[floor(n/2)]+1and all the nodes following it till

nare leaves.

Conclusion: In a Heap having n elements, Elements from indexes **[(floor(n/2)+1) to n]** are leaves.

**What is starting index of leaves if indexes start from 0 instead of 1?**

The above explanation assumes indexes starting from 1, but in most of the programming languages, index starts with 0.

If we consider 0 as starting index, then leaves starts from

floor(n/2)and exist till end, i.e., (n-1).

This article is contributed by **Ranju Kumari**. If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.

Attention reader! Don’t stop learning now. Get hold of all the important DSA concepts with the **DSA Self Paced Course** at a student-friendly price and become industry ready.

## Recommended Posts:

- Print all the leaf nodes of Binary Heap
- Applications of Heap Data Structure
- Convert min Heap to max Heap
- Heap Sort for decreasing order using min heap
- Overview of Data Structures | Set 2 (Binary Tree, BST, Heap and Hash)
- Tournament Tree (Winner Tree) and Binary Heap
- Why is Binary Heap Preferred over BST for Priority Queue?
- How to check if a given array represents a Binary Heap?
- Check if a given Binary Tree is Heap
- Binary Heap
- Array Representation Of Binary Heap
- Given level order traversal of a Binary Tree, check if the Tree is a Min-Heap
- Height of a complete binary tree (or Heap) with N nodes
- Complexity analysis of various operations of Binary Min Heap
- Priority Queue using Binary Heap
- Design an efficient data structure for given operations
- k largest(or smallest) elements in an array | added Min Heap method
- Time Complexity of building a heap
- Binomial Heap
- Fibonacci Heap | Set 1 (Introduction)