This document provides an introduction to data structures and algorithms. It defines key concepts such as data structures, abstract data types, abstraction, and algorithms. Data structures are used to organize data in memory to solve problems, while algorithms are the step-by-step processes used to manipulate data structures. Programs consist of both data structures and algorithms. The document also outlines properties that algorithms must have such as being finite, definite, sequential, feasible, correct, independent of language, complete, effective, and having specified input/output.
Download Complete Material - https://www.instamojo.com/prashanth_ns/
This Data Structures and Algorithms contain 15 Units and each Unit contains 60 to 80 slides in it.
Contents…
• Introduction
• Algorithm Analysis
• Asymptotic Notation
• Foundational Data Structures
• Data Types and Abstraction
• Stacks, Queues and Deques
• Ordered Lists and Sorted Lists
• Hashing, Hash Tables and Scatter Tables
• Trees and Search Trees
• Heaps and Priority Queues
• Sets, Multi-sets and Partitions
• Dynamic Storage Allocation: The Other Kind of Heap
• Algorithmic Patterns and Problem Solvers
• Sorting Algorithms and Sorters
• Graphs and Graph Algorithms
• Class Hierarchy Diagrams
• Character Codes
Data may be organized in many different ways; the logical or mathematical model of a particular organization of data is called "Data Structure". The choice of a particular data model depends on two considerations:
It must be rich enough in structure to reflect the actual relationships of the data in the real world.
The structure should be simple enough that one can effectively process the data when necessary.
Data Structure Operations
The particular data structure that one chooses for a given situation depends largely on the nature of specific operations to be performed.
The following are the four major operations associated with any data structure:
i. Traversing : Accessing each record exactly once so that certain items in the record may be processed.
ii. Searching : Finding the location of the record with a given key value, or finding the locations of all records which satisfy one or more conditions.
iii. Inserting : Adding a new record to the structure.
iv. Deleting : Removing a record from the structure.
Primitive and Composite Data Types
Primitive Data Types are Basic data types of any language. In most computers these are native to the machine's hardware.
Some Primitive data types are:
Integer
In this educational video, we will provide an introduction to data structures. You will learn what data structures are, including queues, stacks, trees, and binary search. We will explore different types of data structures and specifically dive into priority queues. By watching this ppt, you will gain knowledge and have the opportunity to improve your command of data structures. Don't miss this chance to learn something new and expand your understanding.
C++ is an enhanced version of the C language. C++ includes everything that is part of C language and adds support for object oriented programming (OOP). With very few, very major exceptions, C++ is a superset of C
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Download Complete Material - https://www.instamojo.com/prashanth_ns/
This Data Structures and Algorithms contain 15 Units and each Unit contains 60 to 80 slides in it.
Contents…
• Introduction
• Algorithm Analysis
• Asymptotic Notation
• Foundational Data Structures
• Data Types and Abstraction
• Stacks, Queues and Deques
• Ordered Lists and Sorted Lists
• Hashing, Hash Tables and Scatter Tables
• Trees and Search Trees
• Heaps and Priority Queues
• Sets, Multi-sets and Partitions
• Dynamic Storage Allocation: The Other Kind of Heap
• Algorithmic Patterns and Problem Solvers
• Sorting Algorithms and Sorters
• Graphs and Graph Algorithms
• Class Hierarchy Diagrams
• Character Codes
Data may be organized in many different ways; the logical or mathematical model of a particular organization of data is called "Data Structure". The choice of a particular data model depends on two considerations:
It must be rich enough in structure to reflect the actual relationships of the data in the real world.
The structure should be simple enough that one can effectively process the data when necessary.
Data Structure Operations
The particular data structure that one chooses for a given situation depends largely on the nature of specific operations to be performed.
The following are the four major operations associated with any data structure:
i. Traversing : Accessing each record exactly once so that certain items in the record may be processed.
ii. Searching : Finding the location of the record with a given key value, or finding the locations of all records which satisfy one or more conditions.
iii. Inserting : Adding a new record to the structure.
iv. Deleting : Removing a record from the structure.
Primitive and Composite Data Types
Primitive Data Types are Basic data types of any language. In most computers these are native to the machine's hardware.
Some Primitive data types are:
Integer
In this educational video, we will provide an introduction to data structures. You will learn what data structures are, including queues, stacks, trees, and binary search. We will explore different types of data structures and specifically dive into priority queues. By watching this ppt, you will gain knowledge and have the opportunity to improve your command of data structures. Don't miss this chance to learn something new and expand your understanding.
C++ is an enhanced version of the C language. C++ includes everything that is part of C language and adds support for object oriented programming (OOP). With very few, very major exceptions, C++ is a superset of C
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
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Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
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This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
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Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
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http://sandymillin.wordpress.com/iateflwebinar2024
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Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
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Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
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3. Introduction to Data Structures and Algorithms Analysis
A program
A set of instruction which is written in order
to solve a problem.
A solution to a problem actually consists of
two things:
A way to organize the data
Sequence of steps to solve the problem
3
4. 4
The way data are organized in a computers
memory is said to be Data Structure.
The sequence of computational steps to solve a
problem is said to be an Algorithm.
Therefore, a program is Data structures plus
Algorithm.
Introduction....(continued)
5. Introduction to Data Structures
Data structures are used to model the world or part of
the world. How?
1. The value held by a data structure represents some specific
characteristic of the world.
2. The characteristic being modeled restricts the possible values
held by a data structure and the operations to be performed
on the data structure
The first step to solve the problem is obtaining
ones own abstract view, or model, of the
problem.
This process of modeling is called abstraction.
5
7. Abstraction
Abstraction is a process of classifying characteristics as
relevant and irrelevant for the particular purpose at hand
and ignoring the irrelevant ones.
Example: model students of DDU.
Relevant:
Char Name[15];
Char ID[11];
Char Dept[20];
int Age, year;
Non relevant
float hight, weight;
7
8. 8
Using the model, a programmer tries to
define the properties of the problem.
These properties include
The data which are affected and
The operations that are involved in the problem
An entity with the properties just described
is called an abstract data type (ADT).
Abstraction....(continued)
9. 9
Abstract Data Types
Consists of data to be stored and operations supported on
them.
Is a specification that describes a data set and the
operation on that data.
The ADT specifies:
What data is stored.
What operations can be done on the data.
Does not specify how to store or how to implement the
operation.
Is independent of any programming language
10. 10
Example: ADT employees of an organization:
This ADT stores employees with their relevant attributes
and discarding irrelevant attributes.
Relevant:- Name, ID, Sex, Age, Salary, Dept, Address
Non Relevant :- weight, color, height
This ADT supports hiring, firing, retiring, …
operations.
ADT....(continued)
11. 11
Data Structure
In Contrast a data structure is a language
construct that the programmer has defined in
order to implement an abstract data type.
What is the purpose of data structures in programs?
Data structures are used to model a problem.
12. 12
Data Structure
Example:
struct Student_Record
{
char name[20];
char ID_NO[10];
char Department[10];
int age;
};
Attributes of each variable:
Name: Textual label.
Address: Location in memory.
Scope: Visibility in statements of a program.
Type: Set of values that can be stored + set of operations that can be performed.
Size: The amount of storage required to represent the variable.
Life time: The time interval during execution of a program while the variable exists.
13. 13
Algorithm
Is a brief specification of an operation for solving a
problem.
is a well-defined computational procedure that takes
some value or a set of values as input and produces
some value or a set of values as output.
Inputs Algorithm Outputs
An algorithm is a specification of a behavioral
process. It consists of a finite set of instructions that
govern behavior step-by-step.
Is part of what constitutes a data structure
14. 14
Data structures model the static part of the world.
They are unchanging while the world is changing.
In order to model the dynamic part of the world
we need to work with algorithms.
Algorithms are the dynamic part of a program’s
world model.
Algorithm
15. 15
An algorithm transforms data structures from one
state to another state.
What is the purpose of algorithms in programs?
Take values as input. Example: cin>>age;
Change the values held by data structures. Example: age=age+1;
Change the organization of the data structure:
Example:
Sort students by name
Produce outputs:
Example: Display student’s information
Algorithm
16. 16
The quality of a data structure is related to its
ability to successfully model the characteristics
of the world (problem).
Similarly, the quality of an algorithm is related
to its ability to successfully simulate the
changes in the world.
Algorithm
17. 17
However, the quality of data structure and algorithms
is determined by their ability to work together well.
Generally speaking, correct data structures lead to
simple and efficient algorithms.
And correct algorithms lead to accurate and efficient
data structures.
Algorithm
18. 18
Properties of Algorithms
Algorithm must complete after a finite number of
steps.
Algorithm should have a finite number of
steps.
Finite int i=0; Infinite while(true){
while(i>10){ cout<<“Hello”;
cout<< i; }
i++;
}
Finiteness:
19. 19
Definiteness (Absence of ambiguity):
Each step must be clearly defined, having
one and only one interpretation.
At each point in computation, one should be
able to tell exactly what happens next.
20. 20
Sequential:
Each step must have a uniquely defined
preceding and succeeding step.
The first step (start step) and last step (halt
step) must be clearly noted.
21. 21
Feasibility:
It must be possible to perform each
instruction.
Each instruction should have possibility to
be executed.
1) for(int i=0; i<0; i++){
cout<< i; // there is no possibility
} that this statement to
be executed.
2) if(5>7) {
cout<<“hello”; // not executed.
}
22. 22
Correctness
It must compute correct answer for all
possible legal inputs.
The output should be as expected and required and
correct.
It must not depend on any one programming
language.
It must solve the problem completely.
Language Independence:
Completeness:
23. 23
Effectiveness:
Doing the right thing. It should yield the correct
result all the time for all of the possible cases.
It must solve with the least amount of
computational resources such as time and
space.
Producing an output as per the requirement
within the given resources (constraints).
Efficiency:
24. 24
Example:
Write a program that takes a number and displays
the square of the number.
1) int x;
cin>>x;
cout<<x*x;
2) int x,y;
cin>>x;
y=x*x;
cout<<y;
25. 25
Example:
Write a program that takes two numbers and
displays the sum of the two.
Program a Program b Program c
cin>>a; cin>>a; cin>>a;
cin>>b; cin>>b; cin>>b;
sum = a+b; a = a+b; cout<<a+b;
cout<<sum; cout<<a;
Which one is most efficient and which are effective?
Program c the most efficient
All are effective but with different efficiencies.
26. 26
Input/output:
There must be a specified number of input
values, and one or more result values.
Zero or more inputs and one or more outputs.
A good general rule is that each step should carry out one
logical step.
What is simple to one processor may not be simple to another.
Simplicity:
27. Next Class
Complexity Analysis
Formal Approach to Analysis
Asymptotic Analysis
The Big-Oh Notation
Big-Omega Notation
Theta Notation
Algorithm Analysis Concepts
27