The document defines basic terminology related to data structures, including datum, data, information, knowledge, entity, attribute, field, record, and file. It explains that data are organized hierarchically into fields, records, and files. Common data structure types are introduced, including arrays, linked lists, stacks, queues, graphs, and trees. Key operations on data structures like traversal, search, insertion, deletion, sorting, and merging are also outlined. The document provides examples and discusses the need for efficient data structures to solve complex computing problems within space and time constraints.

1. Data Structure : Unit 1
By AMAR JEET RAWAT
HoD, Dept. of IT
Alpine Institute of Management & Technology

2. Basic Terminology
• Datum : Singular form of data , refers to single
unit of values. e.i. 1,4,A,z,& etc.
• Data : Data are simply values or set of values.
It’s a collection of data items. i.e. 45741,BX6T
• Information : Processed data which provide
some meaning. e.i. Roll no : 45741.
• Knowledge : Collection of related information.
– Your name is Alok . Your roll no is 45741.

3. Basic Terminology
• Entity : Some object that has certain attributes
or properties which may be assigned values.
• Entity Set: Entities having similar attributes.
– All employees from an entity set.
Attribute Name Age Gender ID Number
Values Alok 23 Male 2401-12-A6

4. Basic Terminology
Data are organizes into the hierarchy of fields,
records and files which reflect some relationship
between attributes, entities and entity set.
• Field : is a single elementary unit of information
representing an attribute of an entity.
• Record : is the collection of field values of given
entity.
• File: is collection of records of entities in a set of
entity.

5. Example
Roll No Name Class Age Contact
1120100 Alok Kumar BCA-2 20 963852741
1120101 Tarun BCA-2 21 789541621
1120102 Pooja B.Sc(IT)-4 20 745241624
Attributes
field
Record
File

6. Records Types
• Fixed Length Records: All the records contain
the same data items with the same amount of
space assigned to each data item.
• Variable Length Records: These records
contain data items with different amount of
space assigned to each data item.

7. Study of Data Structure includes
• Logical or mathematical description of the
structure
• Implementation of the structure on a
computer
• Quantitative analysis of the structure to
determine the amount of memory(space)
needed to store the structure and time
required (time) to process the structure.

8. Data Structure
• Logical or mathematical model of a particular
organization of data is called data structure.

9. 9
The Need for Data Structures
Data structures organize data
 more efficient programs.
More powerful computers  more complex
applications.
More complex applications demand more
calculations.
Complex computing tasks are unlike our
everyday experience.

10. 10
Efficiency
A solution is said to be efficient if it solves
the problem within its resource constraints.
– Space
– Time
• The cost of a solution is the amount of
resources that the solution consumes.

11. 11
Data Structure Philosophy
Each data structure has costs and benefits.
Rarely is one data structure better than
another in all situations.
A data structure requires:
– space for each data item it stores,
– time to perform each basic operation,
– programming effort.

12. 12
Data Structure Philosophy (cont)
Each problem has constraints on available
space and time.
Only after a careful analysis of problem
characteristics can we know the best data
structure for the task.
Bank example:
– Start account: a few minutes
– Transactions: a few seconds
– Close account: overnight

13. 13
Logical vs. Physical Form
Data items have both a logical and a
physical form.
Logical form: definition of the data item
within an ADT.
– Ex: Integers in mathematical sense: +, -
Physical form: implementation of the data
item within a data structure.
– Ex: 16/32 bit integers, overflow.

14. Data Structure Types

15. Linear Data Structure
• A data structure is said to be linear if its
elements form a sequence or a linear list.
– Array
– Link List
– Stack
– Queue

16. Array
• Collection of similar finite elements.
– Collection of integers
– Collection of images.
• Simplest type of data structure.
• Types of Arrays
– Singular or simple Array.
– Multidimensional Array

18. Data Structure Operations
• Traversal : Visit every part of the data structure
• Search : Traversal through the data structure for a given
element
• Insertion : Adding new elements to the data structure
• Deletion : Removing an element from the data structure.
• Sorting : Rearranging the elements in some type of
order(e.g Increasing or Decreasing)
• Merging : Combining two similar data structures into one

19. Stack
• Stack is an ordered list of objects.
• Stack is based on LIFO (Last in first out)

20. Queue
• It is an ordered list of elements n , such that
n>0 in which all deletions are made at one
end called the front end and all insertions
at the other end called the rear end .
• Theoperational semantic of queue is FIFO i.e.
first in first out

21. Example

22. Link List
• Linked List is a linear data structure which
consists of group of nodes in a sequence
which is divided in two parts.
• Each node consists of its own data and the
address of the next node and forms a chain.
Linked Lists are used to create trees and
graphs.

23. Non-Linear Data Structure
• The Data structure is said to be Non-Linear
Data Structures if it's elements do not form a
sequence or a linear series but form a
hierarchical format.
– Graphs
– Tree

24. Graph
• Graph is an ordered pair G=(V,E), where
– V: set of vertices ,nodes , points
– E: set of edges , arcs, lines

25. Link List