Data Structure Introduction chapter 1

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A data structure is a way of organizing and storing data in a computer so that it can be accessed and manipulated efficiently. The document discusses how data structures help handle complex algorithms and data volumes, optimize memory usage, and allow code reuse through libraries. Common linear data structures include arrays, linked lists, stacks, and queues, while non-linear structures include trees. Data structures are a fundamental part of computer science and are used widely in areas like artificial intelligence, operating systems, and graphics.

Data Structure
The logical or mathematical model of a particular
organization of data is called a data structure. The
data structure is a way of storing and accessing the
data into an acceptable form for computers. So that
a large number of data is processed in a small
interval of time. In a simple way, we say that storing
the data into computer memory is called a data
structure.
A data structure is a particular way of organizing
data in a computer so that it can be used effectively.

References
• Data Structures and Algorithms Made Easy: Data Structures
and Algorithmic Puzzles” is a book written by Narasimha
Karumanchi
• "Introduction to Algorithms" by Thomas H Cormen, Charles
E Leiserson, Ronald L Rivest and Clifford Stein ( CLRS )
• Algorithms & Data Structures" By Robert Lafore : C based
• “Advanced Data Structures" by Jonas Lowgren – C++ based
• Computer Science Distilled" By Peter Alfredsen C++ based
• "Introduction to Algorithms" by Robert Sedgewick - Java
• "Data Structures and Network Algorithms" By Sanjoy
Dasgupta, Christos H Papadimitriou, Umesh V Vazirani

Data Structure
The data structure is a key component of computer
science and is largely used in the area of AI, OS, graphics
etc. DS store objects and allow their manipulation on the
basis of two different types linear or non-linear.
Data structure and algorithms help in understanding the
nature of the problem at a deeper level and thereby a
better understanding of the world.

• Handling complexity: Increase in complexities in computer algorithms, the
volume of data usage is rising; this can affect the execution of the
application and can create remarkable areas of concern like processing
speed, data search, and multiple requests. To counter these data
structures are used.
• Systematic memory use: Systematic application of data structure memory
usage can be optimized, e.g., we can use linked list vs. arrays when we are
not particular about the data size. When there is no longer use of memory,
it can be cleared.
• Ability to reuse: Once we have executed a particular data structure, we
can reuse it in any distinct position. Implementation of data structures can
be assembled into libraries that can be utilized by various clients.
• Abstraction: Data structure acts as the foundation of abstract data types;
the data structure describes the physical form of Abstract Data Type. In
ADT, the set of operations is supposed to be understood, and the data
structure provides physicality to them.
Data structures are the integral constituent of any programming language or
complex computations. Mostly, structured data structures are crucial to
designing efficient algorithms.

Types of Data structures
Linear Data structure: If the elements of a data structure
result in a sequence or a linear list then it is called a
Linear data structure. Every data element is connected to
its next and sometimes previous element in a sequential
manner. Example - Arrays, Linked Lists, Stacks, Queues,
etc.
Non-linear Data structure: If the elements of a Data
structure result in a way that the traversal of nodes is not
done in a sequential manner, then it is a Non-linear data
structure. Its elements are not sequentially connected,
and every element can attach to another element in
multiple ways. Example - Hierarchical data structure like
trees.

Linear Data Structures
A data structure is a particular way of organizing
data in a computer so that it can be used
effectively. The idea is to reduce the space and
time complexities of different tasks. Below is an
overview of some popular linear data structures.
1. Array
2. Linked List
3. Stack
4. Queue

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Data Structure Introduction chapter 1

1. Data Structure Dr. V Dutta

2. Data Structure The logical or mathematical model of a particular organization of data is called a data structure. The data structure is a way of storing and accessing the data into an acceptable form for computers. So that a large number of data is processed in a small interval of time. In a simple way, we say that storing the data into computer memory is called a data structure. A data structure is a particular way of organizing data in a computer so that it can be used effectively.

3. References • Data Structures and Algorithms Made Easy: Data Structures and Algorithmic Puzzles” is a book written by Narasimha Karumanchi • "Introduction to Algorithms" by Thomas H Cormen, Charles E Leiserson, Ronald L Rivest and Clifford Stein ( CLRS ) • Algorithms & Data Structures" By Robert Lafore : C based • “Advanced Data Structures" by Jonas Lowgren – C++ based • Computer Science Distilled" By Peter Alfredsen C++ based • "Introduction to Algorithms" by Robert Sedgewick - Java • "Data Structures and Network Algorithms" By Sanjoy Dasgupta, Christos H Papadimitriou, Umesh V Vazirani

7. Data Structure The data structure is a key component of computer science and is largely used in the area of AI, OS, graphics etc. DS store objects and allow their manipulation on the basis of two different types linear or non-linear. Data structure and algorithms help in understanding the nature of the problem at a deeper level and thereby a better understanding of the world.

8. • Handling complexity: Increase in complexities in computer algorithms, the volume of data usage is rising; this can affect the execution of the application and can create remarkable areas of concern like processing speed, data search, and multiple requests. To counter these data structures are used. • Systematic memory use: Systematic application of data structure memory usage can be optimized, e.g., we can use linked list vs. arrays when we are not particular about the data size. When there is no longer use of memory, it can be cleared. • Ability to reuse: Once we have executed a particular data structure, we can reuse it in any distinct position. Implementation of data structures can be assembled into libraries that can be utilized by various clients. • Abstraction: Data structure acts as the foundation of abstract data types; the data structure describes the physical form of Abstract Data Type. In ADT, the set of operations is supposed to be understood, and the data structure provides physicality to them. Data structures are the integral constituent of any programming language or complex computations. Mostly, structured data structures are crucial to designing efficient algorithms.

9. Types of Data structures Linear Data structure: If the elements of a data structure result in a sequence or a linear list then it is called a Linear data structure. Every data element is connected to its next and sometimes previous element in a sequential manner. Example - Arrays, Linked Lists, Stacks, Queues, etc. Non-linear Data structure: If the elements of a Data structure result in a way that the traversal of nodes is not done in a sequential manner, then it is a Non-linear data structure. Its elements are not sequentially connected, and every element can attach to another element in multiple ways. Example - Hierarchical data structure like trees.

10. Linear Data Structures A data structure is a particular way of organizing data in a computer so that it can be used effectively. The idea is to reduce the space and time complexities of different tasks. Below is an overview of some popular linear data structures. 1. Array 2. Linked List 3. Stack 4. Queue

Data Structure Introduction chapter 1

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Data Structure Introduction chapter 1