Introduction to data structures

1. Introduction to Data Structures
• Introduction to Data Structures
• Basic terminologies
• Need and Applications
• Classification of data structures
• Operations on data structures
• Abstract Data Types

2. What is Data Structure?
• Data – Basic fact or entity utilized in calculation or
manipulation or collection of raw facts.
• A data structure is a systematic way of organizing and
accessing data.
• Logical or mathematical model of a particular organization of
data is called data structure.
• In computer science, a data structure is a particular way of
storing and organizing data in a computer’s memory so that it
can be used efficiently.

3. What is Data Structure?
• Data structure affects the design of both structural &
functional aspects of a program.
Program=algorithm + Data Structure
• Algorithm is a step by step procedure to solve a particular
function.

4. Need of data structure
• It gives different level of organization data.
• It tells how data can be stored and accessed
in its elementary level.
• Provide operation on group of data, such as
adding an item, looking up highest priority
item.
• Provide a means to manage huge amount of
data efficiently.
• Provide fast searching and sorting of data.

5. Areas in which data structures are applied
extensively
• Compiler Design
• Operating System
• Database Management System
• Statistical analysis package
• Numerical Analysis
• Graphics
• Artificial Intelligence
• Simulation

6. Classification of data structure
• Data structure are normally divided into two
broad categories:
1. Primitive Data Structure
2. Non-Primitive Data Structure

7. Classification of data structure

8. Primitive data structure
• These are basic structures and directly operated
upon by the machine instructions.
• Data structures that are directly operated upon the
machine-level instructions are known as primitive
data structures.
• Integer, Floating-point number, Character constants,
string constants, pointers etc, fall in this category.

9. Non-primitive data structure
• The Data structures that are derived from the
primitive data structures are called Non-primitive
data structure.
• The non-primitive data structures emphasize on
structuring of a group of homogeneous (same type)
or heterogeneous (different type) data items.
It’s further classified in linear and nonlinear data
structure.
a) Linear data structure: In linear data structure the
item are arrange in linear sequence like an array.
b) Nonlinear data structure: In this data structure
items are not in sequence.

10. Linear data structure
Data structure is said to be linear if the
elements form a sequence.
i.e., while traversing sequentially, we can reach
only one element directly from another.
For example : Stack, Linked list, Queue etc.

12. Non linear data structure
• elements in a nonlinear data structure do not
form a sequence
• i.e each item or element may be connected
with two or more other items or elements in a
non-linear arrangement
• For example : Graphs, Trees etc.

14. Non-Primitive data structure
1.Static Data Structure : Static data structure are those whose
size and structure associated with memory location are fixed
at compile time . e.g. Array int no[5]
2.Dynamic Data Structure : Dynamic structures are those which
expand or shrink as required during the program execution.
e.g. Link List

15. Description of various
Data Structures : Arrays
• An array is defined as a set of finite
number of homogeneous elements or
same data items.
• It means an array can contain one type of
data only, either all integer, all float-point
number or all character.

16. Arrays
• Simply, declaration of array is as follows:
int arr[10]
• Where int specifies the data type or type of
elements arrays stores.
• “arr” is the name of array & the number
specified inside the square brackets is the
number of elements an array can store, this is
also called sized or length of array.

17. Arrays
• Following are some of the concepts to be
remembered about arrays:
–The individual element of an array can
be accessed by specifying name of the
array, following by index or subscript
inside square brackets.
–The first element of the array has index
zero[0]. It means the first element and
last element will be specified as:arr[0]
& arr[9]
Respectively.

18. Arrays
–The elements of array will always be
stored in the consecutive (continues)
memory location.
–The number of elements that can be stored
in an array, that is the size of array or its
length is given by the following equation:
(Upperbound-lowerbound)+1

19. Arrays
–For the above array it would be
(9-0)+1=10,where 0 is the lower
bound of array and 9 is the upper
bound of array.
–Array can always be read or written
through loop. If we read a one-
dimensional array it require one loop
for reading and other for writing the
array.

20. Arrays
–For example: Reading an array
For(i=0;i<=9;i++)
scanf(“%d”,&arr[i]);
–For example: Writing an array
For(i=0;i<=9;i++)
printf(“%d”,arr[i]);

21. Arrays
–If we are reading or writing two-
dimensional array it would require two
loops. And similarly the array of a N
dimension would required N loops.
–Some common operation performed on
array are:
• Creation of an array
• Traversing an array

22. Arrays
• Insertion of new element
• Deletion of required element
• Modification of an element
• Merging of arrays

23. Lists
• A lists (Linear linked list) can be defined as a
collection of variable number of data items.
• Lists are the most commonly used non-
primitive data structures.
• An element of list must contain at least two
fields, one for storing data or information and
other for storing address of next element.
• As you know for storing address we have a
special data structure of list the address must
be pointer type.

24. Lists
• Technically each such element is referred
to as a node, therefore a list can be
defined as a collection of nodes as show
bellow:
Head
AAA BBB CCC
Information field Pointer field
[Linear Liked List]

25. Lists
• Types of linked lists:
– Single linked list
– Doubly linked list
– Single circular linked list
– Doubly circular linked list

26. Stack
• A stack is also an ordered collection of
elements like arrays, but it has a special
feature that deletion and insertion of
elements can be done only from one end
called the top of the stack (TOP)
• Due to this property it is also called as last
in first out type of data structure (LIFO).

27. Stack
• It could be through of just like a stack of plates
placed on table in a party, a guest always takes
off a fresh plate from the top and the new plates
are placed on to the stack at the top.
• It is a non-primitive data structure.
• When an element is inserted into a stack or
removed from the stack, its base remains fixed
where the top of stack changes.

28. Stack
• Insertion of element into stack is called
PUSH and deletion of element from stack
is called POP.
• The bellow show figure how the
operations take place on a stack:
PUSH POP
[STACK]

29. Stack
• The stack can be implemented into two
ways:
–Using arrays (Static implementation)
–Using pointer (Dynamic
implementation)

30. Queue
• Queue are first in first out type of data
structure (i.e. FIFO)
• In a queue new elements are added to the
queue from one end called REAR end and
the element are always removed from other
end called the FRONT end.
• The people standing in a railway reservation
row are an example of queue.

31. Queue
• Each new person comes and stands at the
end of the row and person getting their
reservation confirmed get out of the row
from the front end.
• The bellow show figure how the
operations take place on a stack:
10 20 30 40 50
front rear

32. Queue
• The queue can be implemented into two
ways:
–Using arrays (Static implementation)
–Using pointer (Dynamic
implementation)

33. Trees
• A tree can be defined as finite set of data
items (nodes).
• Tree is non-linear type of data structure in
which data items are arranged or stored in
a sorted sequence.
• Tree represent the hierarchical
relationship between various elements.

34. Trees
• In trees: There is a special data item at the
top of hierarchy called the Root of the tree.
• The remaining data items are partitioned into
number of mutually exclusive subset, each of
which is itself, a tree which is called the sub
tree.
• The tree always grows in length towards
bottom in data structures, unlike natural trees
which grows upwards.

35. Trees
• The tree structure organizes the data into
branches, which related the information.
A
B C
D E F G
root

36. Graph
• Graph is a mathematical non-linear data
structure capable of representing many
kind of physical structures.
• It has found application in Geography,
Chemistry and Engineering sciences.
• Definition: A graph G(V,E) is a set of
vertices V and a set of edges E.

37. Graph
• An edge connects a pair of vertices and
many have weight such as length, cost and
another measuring instrument for
according the graph.
• Vertices on the graph are shown as point
or circles and edges are drawn as arcs or
line segment.

38. Graph
• Example of graph:
v2
v1
v4
v5
v3
10
15
8
6
11
9
v4
v1
v2
v4
v3
[a] Directed &
Weighted Graph
[b] Undirected Graph

39. Graph
• Types of Graphs:
–Directed graph
–Undirected graph
–Simple graph
–Weighted graph
–Connected graph
–Non-connected graph

40. Quiz
• Classify following data structures in linear and
non linear
1. Tree
2. Array
3. Linked List
4. Stack
5. Graph
6. Queue

41. DATA STRUCTURE OPERATIONS
• data structure is used for the storage of data
in computer so that data can be used efficiently
• The data manipulation within the data structures are
performed by means of certain operations
The following operations play a major role on data structures.
a) Traversing : accessing each data exactly once so that each
data items is traversed or visited.
b) Searching : finding the location of the data within data
structure which satisfy searching condition or criteria.

42. c) Inserting : adding a new data in the data structure.
d) Deleting : removing a data from the data structure.
Sometimes two or more of these operations may be used in a
given situation. For example, if we want to delete a record
with a given key value, at first we will have need to search for
the location of the record and then delete that record.

43. • The following two operations are also used in some special
situations :
e) Sorting : Arranging the data in some logical order e. g.,
increasing or decreasing, with numerical data, or
alphabetically, with character data.
f) Merging : combining the data of two different sorted files
into a single sorted file.

44. MCQ

45. 1. List out the areas in which data structures
are applied extensively? (asked in TCS)
2. What is Data Structure?
3 Which are the types of data structure? State
the type of array data structure.
4. What is the need of data structure?

46. 12.46
Abstract Data Type
Problem solving with a computer means processing
data. To process data, we need to define the data type
and the operation to be performed on the data. The
definition of the data type and the definition of the
operation to be applied to the data is part of the idea
behind an abstract data type (ADT)—to hide how the
operation is performed on the data. In other words, the
user of an ADT needs only to know that a set of
operations are available for the data type, but does not
need to know how they are applied.

47. Abstract Data Type
• Collection of data items together with the
operations on the data.
• The word “abstract” refers to the fact that the
data and the basic operations defined on it
are being studied independently of how they
are implemented.
• It involves what can be done with the data,
not how has to be done.

48. Abstract Data Type
• When we use ADT our program divided into 2
parts:
• 1. The Application
• 2 The Implementation
Application
Specification
Implementation
Uses ADT
Defines ADT
Implements ADT