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Practice Problems on Heap
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A Heap is a special Tree-based data structure in which the tree is a complete binary tree.
Heap Data Structure
Operations of Heap Data Structure:
- Heapify: a process of creating a heap from an array.
- Insertion: process to insert an element in existing heap time complexity O(log N).
- Deletion: deleting the top element of the heap or the highest priority element, and then organizing the heap and returning the element with time complexity O(log N).
- Peek: to check or find the first (or can say the top) element of the heap.
Types of Heap Data Structure
Generally, Heaps can be of two types:
- Max-Heap: In a Max-Heap the key present at the root node must be greatest among the keys present at all of it’s children. The same property must be recursively true for all sub-trees in that Binary Tree.
- Min-Heap: In a Min-Heap the key present at the root node must be minimum among the keys present at all of it’s children. The same property must be recursively true for all sub-trees in that Binary Tree.
- Introduction to Heap – Data Structure and Algorithm Tutorials
- Binary Heap
- Applications, Advantages and Disadvantages of Heap
- Time Complexity of building a heap
- Applications of Heap Data Structure
- Comparison between Heap and Tree
- When building a Heap, is the structure of Heap unique?
Some other types of Heap:
- Binomial Heap
- Fibonacci Heap
- Leftist Heap
- K-ary Heap
Standard problems on Heap:
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