Representation of max-heap sequentially, Data Structure & Algorithms

Assignment Help:

Q. How do we represent a max-heap sequentially? Explain by taking a valid   example.        

Ans:

A max heap is also called as a descending heap, of size n is an almost complete binary tree of n nodes such as the content of each node is less than or equal to the content or matter of its father. If sequential representation of an almost whole binary tree is used, this condition reduces to the condition of inequality.

Info[j] <= info[(j-1)/2] for 0 <= ((j-1)/2) < j <= n-1

It is very much clear from this definition that root of the tree contains the largest element in the heap in the descending heap. Any of the paths from the root to a leaf is an ordered list in the descending order.


 

 

 

 


Related Discussions:- Representation of max-heap sequentially

Sorting, compare and contrast the bubble sort,quick sort,merge sort and rad...

compare and contrast the bubble sort,quick sort,merge sort and radix sort

Advanced data structures - splay trees, This is a unit of which targeted on...

This is a unit of which targeted on the emerging data structures. Red- Black trees, Splay trees, AA-trees & Treaps are introduced. The learner must explore the possibilities of app

Circularly linked lists implementation, CIRCULARLY LINKED LISTS IMPLEMENTAT...

CIRCULARLY LINKED LISTS IMPLEMENTATION A linked list wherein the last element points to the first element is called as CIRCULAR linked list. The chains do not specified first o

Post order traversal, Post order traversal: The children of node are vi...

Post order traversal: The children of node are visited before the node itself; the root is visited last. Each node is visited after its descendents are visited. Algorithm fo

Relationship between shortest path distances of modified, a) Given a digrap...

a) Given a digraph G = (V,E), prove that if we add a constant k to the length of every arc coming out from the root node r, the shortest path tree remains the same. Do this by usin

The complexity ladder, The complexity Ladder: T(n) = O(1). It is ca...

The complexity Ladder: T(n) = O(1). It is called constant growth. T(n) does not raise at all as a function of n, it is a constant. For illustration, array access has this c

Graph, multilist representation of graph

multilist representation of graph

Find the shortest paths from bellman-ford algorithm, a) Find the shortest p...

a) Find the shortest paths from r to all other nodes in the digraph G=(V,E) shown below using the Bellman-Ford algorithm (as taught in class). Please show your work, and draw the f

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd