DATA STRUCTURE: STACK

Question 1

a linear data structure that follows the Last-In-First-Out (LIFO)
principle.

Answer 1

STACKS

Question 2

the last element added to the stack
is the first one to be removed.
• Insertion and deletion allowed only

Answer 2

at one end (top)

Question 3

STACKS OPERATION
 adding an element to the top of the stack

Answer 3

Push (insertion)

Question 4

STACKS OPERATION
 removing the topmost element from the stack

Answer 4

Pop (deletion)

Question 5

STACKS OPERATION
 viewing the topmost element without removing
it

Answer 5

Peek

Question 6

 the stack is full and push operation is
attempted

Answer 6

Overflow state

Question 7

 the stack is empty and we attempt the pop
operation

Answer 7

Underflow state

Question 8

APPLICATIONS AND USE CASES OF STACKS
Stacks are used to evaluate arithmetic expressions, handle operator precedence, and perform infix-to-postfix
conversion.

Answer 8

Expression Evaluation

Question 9

APPLICATIONS AND USE CASES OF STACKS
Stacks are used to implement undo functionality in text
editors, software applications, and interactive environments.

Answer 9

Undo Operations

Question 10

APPLICATIONS AND USE CASES OF STACKS
Stacks are utilized in algorithms that require backtracking,
such as maze-solving and depth-first search.

Answer 10

Backtracking

Question 11

APPLICATIONS AND USE CASES OF STACKS
Stacks play a role in memory management, particularly in managing activation records during program execution.

Answer 11

Memory Management

Question 12

a linear data structure that follows the First-In-First-Out (FIFO) principle.

Answer 12

QUEUES

Question 13

first element added is the first one to be
removed
• It represents a collection of elements in
which elements are added at one end
(rear) and removed from the other end
(front).

Answer 13

Queues

Question 14

 adds an element to the rear (end) of the queue. The
newly added element becomes the last one in the
queue.

Answer 14

queues operations Enqueue (insertion)

Question 15

 removes the element from the front of the queue. The
next element in the queue becomes the new front.

Answer 15

Dequeue (deletion)

Question 16

 view the element at the front of the queue without
removing it.

Answer 16

Peek

Question 17

A non-linear data structure that consists of nodes
and is connected by edges with a hierarchical organization

Answer 17

TREES

Question 18

The nodes in a tree are arranged in a each node can have (zero or more
child nodes)

Answer 18

parent-child
relationship

Question 19

The topmost node in a tree is called the

Answer 19

root node

Question 20

TERMINOLOGY
Each element in a tree. It contains some data and
may have references to its child nodes. T, S, O, Q, etc. are the nodes of the tree.

Answer 20

Node

Question 21

Represents a connection between two nodes. It
defines the relationship between a parent node and its
child node. A line connecting the nodes.

Answer 21

Edge

Question 22

A node that has one or more child nodes. It is
located above its child nodes in the hierarchy.

Answer 22

Parent

Question 23

A node that has a parent node. It is located below
its parent node in the hierarchy. In a tree, every node except the root node is a child node

Answer 23

Child

Question 24

A node that does not have any child nodes. It is also known as a terminal node.

Answer 24

Leaf

Question 25

Nodes that have one or more child
nodes. They are neither leaf nodes nor the root node.

Answer 25

Internal Nodes

Question 26

the total number of children of a node. The
highest degree of the node among all the nodes in a tree
is called the Degree of Tree.

Answer 26

DEGREE

Question 27

the distance of a node from the root.

Answer 27

LEVEL

Question 28

the number of edges from the leaf node to the particular node in the longest path is known as the height of that node. In the tree, the height of the root node is called “Height of Tree”.

Answer 28

Height

Question 29

many edges from the root node to the particular
node are called the depth of the tree. In the tree, the total
number of edges from the root node to the leaf node in
the longest path is known as “Depth of Tree”.

Answer 29

Depth

Question 30

the sequence of nodes and edges from one node
to another node is called the path between those two
nodes. The length of a path is the total number of nodes
in a path

Answer 30

PATH

Question 31

TYPES OF TREES
• In a tree data structure, the root is the first node of the tree. The root node is the initial node of the tree in data structures.
• In the tree data structure, there must be only one root node.

Answer 31

Root Node

Question 32

A node can have any at most two children
• Follows all properties of the tree data structure.
• Binary trees can have at most two child nodes.
• These two children are called the left child and the right child.

Answer 32

BINARY TREES

Question 33

• Follows all properties of the tree data structure
Left node value<= root node <= right m
• The binary search tree has a unique property known as the binary search property. This states that the value of a left child node of the tree should be less than or equal to the parent node value of the tree. And the value of the right child node should be greater than or equal to the parent value.

Answer 33

BINARY SEARCH TREE

Question 34

• Follows all properties of the tree data structure.
• Self-balancing.
• Each node stores a value called a balanced factor, which is the difference in the height of the left sub-tree and right sub-tree.
• All the nodes in the AVL tree must have a balance factor of -1, 0, and 1.

Answer 34

AVL TREE: (Georgy Adelson-Velsky and Landis – inventor)

Question 35

is a special kind of self-balancing search tree in which each node can contain more than one key and can have more than two children.

Answer 35

B-TREE

Question 36

is also known as a height-balanced.

Answer 36

B tree/m-way tree.