algorithams example, Data Structure & Algorithms

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Time complexity, Run time complexity of an algorithm is depend on

Run time complexity of an algorithm is depend on

Two-dimensional array, Two-dimensional array is shown in memory in followin...

Two-dimensional array is shown in memory in following two ways:  1.  Row major representation: To achieve this linear representation, the first row of the array is stored in th

What are the structures used in file-system implementation, What are the st...

What are the structures used in file-system implementation? Several on-disk and in-memory structures are used to execute a file system a. On-disk structure include P

Properties of red- black tree, Any Binary search tree has to contain follow...

Any Binary search tree has to contain following properties to be called as a red- black tree. 1. Each node of a tree must be either red or black. 2. The root node is always b

What is a linear array, What is a linear array? An array is a way to re...

What is a linear array? An array is a way to reference a series of memory locations using the similar name. Every memory location is shown by an array element. An  array elemen

Bst created in pre- order, Q. Make a BST for the given sequence of numbe...

Q. Make a BST for the given sequence of numbers. 45,32,90,34,68,72,15,24,30,66,11,50,10 Traverse the BST formed in  Pre- order, Inorder and Postorder.

What is a binary search tree (bst), What is a Binary Search Tree (BST)? ...

What is a Binary Search Tree (BST)? A binary search tree B is a binary tree every node of which satisfies the three conditions: 1.  The value of the left-subtree of 'x' is le

Shortest path dijkstras algorithm, * Initialise d & pi* for each vertex ...

* Initialise d & pi* for each vertex v within V( g ) g.d[v] := infinity  g.pi[v] := nil g.d[s] := 0; * Set S to empty * S := { 0 }  Q := V(g) * While (V-S)

Define order of growth, Define order of growth The  efficiency  analysi...

Define order of growth The  efficiency  analysis  framework  concentrates   on  the  order  of  growth  of  an  algorithm's   basic operation count as the principal indicator o

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