Classification of Data Structure

1. Dr.Babasaheb Ambedkar Marathwada University,
Aurangabad
Advances in Data Structure & Algorithms
Dr.Kaveri Lad
Assistant Professor(MCA)
Department of Management Science
Dr.Babsaheb Ambedkar Marathwada University,
Auranagabad
Introduction to Data Structure

2. CONTENTS
Unit-V
Managing Input / Output Files in JAVA : streams, streams classes, Byte streams classes , reading and writing characters , bytes, Random Access Files
, Interactive I/p and o/p,
Reflection API- class identification, interface identification, parent class information and methods information.
• Data Structure – Definition & Types
• Algorithms – Definition and Examples
• Time Complexity
• Asymptotic Notations and Its types

3. Data Structure
Data Structure can be defined as the group of data elements which
provides an efficient way of storing and organising data in the computer
System .
Data Structure manipulate the data very efficiently.

4. Classification of Data Structure

5. Difference between Linear & Non-linear Data Structure
Linear Data Structures Non-Linear Data Structures
Elements are ordered in a linear and
sequential manner.
Elements are ordered in a hierarchy.
Only a single level is present. Multiple level data structures are present.
Implementation is relatively easier. Implementation is relatively complicated.
Traversed in a single run Take multiple runs to traverse the data.
Memory utilization is not efficient compared
to non-linear data structures
Memory utilization is efficient.
Examples: array, queue, linked list, etc. Example: Trees, graphs, etc.
Applications of linear DS are mainly in
application software development.
Applications of non-linear DS are in
Artificial Intelligence and image
processing.

6. Algorithm
” A set of rules to be followed in calculations or other problem-solving
operations ” Or ” A procedure for solving a mathematical problem in a finite
number of steps that frequently by recursive operations “.
Algorithms can be simple or complex, it depends on nature of the problems

7. Steps to write Algorithm -> Program
1. Formulation of Problem
2. Algorithm
3. Flowchart
4. Program

8. Example to write Algorithm -> Program
Write an Algorithm to find the area of Circle
Formula : Area = PI * R*R
Where pi =3.14
Algorithm :
1 Start
2 Assign PI = 3.14
3 Input R
4 Area = PI * R * R
5 Print Area
6 End

9. Example to write Algorithm -> Program
Write an Algorithm to find the greater number among two
Formula : Logical Operation
Algorithm :
1 Start
2 Input A, B
3 If A > B
Then Print A is greater
Else
Then Print B is greater
4 End

10. Time Complexity of an Algorithms /
Asymptotic analysis of an algorithm
Time complexity of an algorithm signifies the total time required by the
program to run till its completion.
Asymptotic analysis : It refers to defining the mathematical
boundation/framing of its run-time performance.
Using asymptotic analysis :
• Best Case,
• Average Case,
• Worst Case

11. Asymptotic Notations
• Big Oh Notation, Ο
• Omega Notation, Ω
• Theta Notation, θ