ITEC33 Flashcards

1
Q

is a pictorial representation of a set of objects where some pairs of objects are connected by links.

A

GRAPH

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2
Q

The interconnected objects are represented by points

A

VERTICES

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3
Q
  • links that connect the vertices
A

EDGES

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4
Q

Each node of the graph is represented as a

A

VERTEX

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5
Q

represents a path between two vertices or a line between two vertices

A

EDGE

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6
Q

Two node or vertices are adjacent if they are connected to each other through an edge.

A

ADJACENCY

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7
Q

represents a sequence of edges between the two vertices.

A

PATH

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8
Q

Adds a vertex to the graph.

A

ADD VERTEX

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9
Q

Adds an edge between the two vertices of the graph.

A

ADD EDGE

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10
Q

Displays a vertex of the graph.

A

DISPLAY VERTEX

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11
Q

traverses a graph in a depthward motion and uses a stack to remember to get the next vertex to start a search, when a dead end occurs in any iteration

A

DEPTH FIRST TRAVERSAL

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12
Q

traverses a graph in a breadthward motion and uses a queue to remember to get the next vertex to start a search, when a dead end occurs in any iteration.

A

BREADTH FIRST TRAVERSAL

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13
Q

represents the nodes connected by edges

A

TREE

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14
Q

can be defined recursively as a collection of nodes

A

TREE DATA STRUCTURE

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15
Q

represents the descendants of a node.

A

SUBTREE

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16
Q

refers to checking the value of a node when control is on the node

A

VISITING

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17
Q

means passing through nodes in a specific order.

A

TRAVERSING

18
Q

represents the generation of a node. If the root node is at level 0, then its next child node is at level 1, its grandchild is at level 2, and so on.

19
Q

represents a value of a node based on which a search operation is to be carried out for a node.

20
Q

exhibits a special behavior.

A

BINARY SEARCH TREE

21
Q

an element in a tree/create a tree.

22
Q

Searches an element in a tree.

23
Q

Traverses a tree in a pre-order manner.

A

PREORDER TRAVERSAL

24
Q

Traverses a tree in an in-order manner.

A

INORDER TRAVERSAL

25
Traverses a tree in a post-order manner.
POSTORDER TRAVERSAL
26
is a process to visit all the nodes of a tree and may print their values too
TRAVERSAL
27
In this traversal method, the left subtree is visited first, then the root and later the right sub-tree.
IN ORDER TRAVERSAL
28
In this traversal method, the root node is visited first, then the left subtree and finally the right subtree.
PRE ORDER TRAVERSAL
29
In this traversal method, the root node is visited last, hence the name. First we traverse the left subtree, then the right subtree and finally the root node.
POST ORDER TREAVERSAL
30
is a hierarchical data structure in which each node has at most two children generally referred as left child and right child.
BINARY TREE
31
It has a root node and every node has at most two children.
ROOTED BINARY TREE
32
It is a tree in which every node in the tree has either 0 or 2 children
FULL BINARY TREE
33
It is a binary tree in which all interior nodes have two children and all leaves have the same depth or same level
PERFECT BINARY TREE
34
It is a binary tree in which every level, except possibly the last, is completely filled, and all nodes are as far left as possible
COMPLETE BINARY TREE
35
A binary tree is height balanced if it satisfies the following constraints: 1. The left and right subtrees' heights differ by at most one, AND 2. The left subtree is balanced, AND 3. The right subtree is balanced An empty tree is height balanced
BALANCED BINARY TREE
36
It is a tree is where each parent node has only one child node. It behaves like a linked list
DEGENARATE TREE
37
A tree whose elements have at most 2 children is called
BINARY TREE DATA STRUCTURE
38
is a node-based binary tree data structure which has the following properties: 1. The left subtree of a node contains only nodes with keys lesser than the node’s key. 2. The right subtree of a node contains only nodes with keys greater than the node’s key. 3. The left and right subtree each must also be a binary search tree. 4. There must be no duplicate nodes.
BINARY SEARCH TREE
39
The tree always has a root node and further child nodes, whether on the left or right. The algorithm performs all the operations by comparing values with the root and its further child nodes in the left or right sub-tree accordingly
40
Always initiate analyzing tree at the root node and then move further to either the right or left subtree of the root node depending upon the element to be located is either less or greater than the root
SEARCH OPERATION
41
This is a very straight forward operation.
INSERT OPERATION
42
is the most advanced and complex among all other operations
DELETE OPERATION