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Data Structures
Introduction
 That means, algorithm is a set of instruction written to carry out certain tasks &
the data structure is the way of organizing the data with their logical relationship
retained.
 To develop a program of an algorithm, we should select an appropriate data
structure for that algorithm.
 Therefore algorithm and its associated data structures from a program.
Definition
 Data structure is representation of the logical relationship existing between
individual elements of data.
 In other words, a data structure is a way of organizing all data items that
considers not only the elements stored but also their relationship to each other.
Introduction
 Data structure affects the design of both structural & functional aspects of a
program.
Program=algorithm + Data Structure
 You know that a algorithm is a step by step procedure to solve a particular
function.
Classification of Data
Structure
 Data structure are normally divided into two broad categories:
Primitive Data Structure
Non-Primitive Data Structure
Classification of Data
Structure
Non-Primitive DS
Linear List Non-Linear List
Array
Link List Stack
Queue Graph Trees
Classification of Data
Structure
Data structure
Primitive DS Non-Primitive DS
Integer Float Character Pointer
Float
Integer Float
Primitive Data Structure
 There are basic structures and directly operated upon by the
machine instructions.
 In general, there are different representation on different
computers.
 Integer, Floating-point number, Character constants, string
constants, pointers etc, fall in this category.
Non-Primitive Data
Structure
 There are more sophisticated data structures.
 These are derived from the primitive data structures.
 The non-primitive data structures emphasize on structuring of a
group of homogeneous (same type) or heterogeneous (different
type) data items.
Non-Primitive Data
Structure
 The most commonly used operation on data structure are broadly categorized
into following types:
 Create
 Selection
 Updating
 Searching
 Sorting
 Merging
 Destroy or Delete
Non-Primitive Data
Structure
 Lists, Stack, Queue, Tree, Graph are example of non-primitive
data structures.
 The design of an efficient data structure must take operations
to be performed on the data structure.
Different between them
 A primitive data structure is generally a basic structure that is
usually built into the language, such as an integer, a float.
 A non-primitive data structure is built out of primitive data
structures linked together in meaningful ways, such as a or a
linked-list, binary search tree, AVL Tree, graph etc.
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.
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.
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.
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
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.
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]);
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
Arrays
Insertion of new element
Deletion of required element
Modification of an element
Merging of arrays
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.
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]
Lists
 Types of linked lists:
 Single linked list
 Doubly linked list
 Single circular linked list
 Doubly circular linked list
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).
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.
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]
Stack
 The stack can be implemented into two ways:
Using arrays (Static
implementation)
Using pointer (Dynamic
implementation)
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.
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
Queue
 The queue can be implemented into two ways:
Using arrays (Static
implementation)
Using pointer (Dynamic
implementation)
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.
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.
Trees
 The tree structure organizes the data into branches, which
related the information.
A
B C
D E F G
root
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.
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.
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
Graph
 Types of Graphs:
Directed graph
Undirected graph
Simple graph
Weighted graph
Connected graph
Non-connected graph
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DATA STRUCTURE AND ALGORITJM POWERPOINT.ppt

  • 2. Introduction  That means, algorithm is a set of instruction written to carry out certain tasks & the data structure is the way of organizing the data with their logical relationship retained.  To develop a program of an algorithm, we should select an appropriate data structure for that algorithm.  Therefore algorithm and its associated data structures from a program.
  • 3. Definition  Data structure is representation of the logical relationship existing between individual elements of data.  In other words, a data structure is a way of organizing all data items that considers not only the elements stored but also their relationship to each other.
  • 4. Introduction  Data structure affects the design of both structural & functional aspects of a program. Program=algorithm + Data Structure  You know that a algorithm is a step by step procedure to solve a particular function.
  • 5. Classification of Data Structure  Data structure are normally divided into two broad categories: Primitive Data Structure Non-Primitive Data Structure
  • 6. Classification of Data Structure Non-Primitive DS Linear List Non-Linear List Array Link List Stack Queue Graph Trees
  • 7. Classification of Data Structure Data structure Primitive DS Non-Primitive DS Integer Float Character Pointer Float Integer Float
  • 8. Primitive Data Structure  There are basic structures and directly operated upon by the machine instructions.  In general, there are different representation on different computers.  Integer, Floating-point number, Character constants, string constants, pointers etc, fall in this category.
  • 9. Non-Primitive Data Structure  There are more sophisticated data structures.  These are derived from the primitive data structures.  The non-primitive data structures emphasize on structuring of a group of homogeneous (same type) or heterogeneous (different type) data items.
  • 10. Non-Primitive Data Structure  The most commonly used operation on data structure are broadly categorized into following types:  Create  Selection  Updating  Searching  Sorting  Merging  Destroy or Delete
  • 11. Non-Primitive Data Structure  Lists, Stack, Queue, Tree, Graph are example of non-primitive data structures.  The design of an efficient data structure must take operations to be performed on the data structure.
  • 12. Different between them  A primitive data structure is generally a basic structure that is usually built into the language, such as an integer, a float.  A non-primitive data structure is built out of primitive data structures linked together in meaningful ways, such as a or a linked-list, binary search tree, AVL Tree, graph etc.
  • 13. 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.
  • 14. 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.
  • 15. 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.
  • 16. 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
  • 17. 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.
  • 18. 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]);
  • 19. 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
  • 20. Arrays Insertion of new element Deletion of required element Modification of an element Merging of arrays
  • 21. 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.
  • 22. 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]
  • 23. Lists  Types of linked lists:  Single linked list  Doubly linked list  Single circular linked list  Doubly circular linked list
  • 24. 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).
  • 25. 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.
  • 26. 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]
  • 27. Stack  The stack can be implemented into two ways: Using arrays (Static implementation) Using pointer (Dynamic implementation)
  • 28. 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.
  • 29. 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
  • 30. Queue  The queue can be implemented into two ways: Using arrays (Static implementation) Using pointer (Dynamic implementation)
  • 31. 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.
  • 32. 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.
  • 33. Trees  The tree structure organizes the data into branches, which related the information. A B C D E F G root
  • 34. 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.
  • 35. 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.
  • 36. 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
  • 37. Graph  Types of Graphs: Directed graph Undirected graph Simple graph Weighted graph Connected graph Non-connected graph
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