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Notes of electronic of sybsc computer science, Study notes of Computer Science

Sybsc computer science notes of electronic

Typology: Study notes

2023/2024

Available from 12/25/2024

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1.Introduction To Data Structure
i) What is data structure ?
A data structure is a storage that is used to store and organize data. It is a way
of arranging data on a computer so that it can be accessed and updated
efficiently.
A data structure is not only used for organizing the data. It is also used for
processing, retrieving, and storing data.
Classification of Data Structure:
Linear data structure: Data structure in which data elements are arranged
sequentially or linearly, where each element is attached to its previous and
next adjacent elements, is called a linear data structure.
Examples of linear data structures are array, stack, queue, linked list, etc.
Non-linear data structure: Data structures where data elements are not placed
sequentially or linearly are called non-linear data structures. In a non-linear
data structure, we can’t traverse all the elements in a single run only.
Examples of non-linear data structures are trees and graphs.
ii) What is ADT ?
The abstract data type is special kind of data type, whose behavior is defined
by a set of values and set of operations.
The keyword “Abstract” is used as we can use these data types, we can
perform different operations. But how those operations are working that is
totally hidden from the user.
The ADT is made of with primitive data types, but operation logics are hidden.
Some examples of ADT are Stack, Queue and List etc.
Advantages of ADT:
Provides abstraction, which simplifies the complexity of the data structure and
allows users to focus on the functionality.
Allow users to work with data structures without having to know the
implementation details, which can simplify programming and reduce errors
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1.Introduction To Data Structure

i) What is data structure?

A data structure is a storage that is used to store and organize data. It is a way of arranging data on a computer so that it can be accessed and updated efficiently. A data structure is not only used for organizing the data. It is also used for processing, retrieving, and storing data. Classification of Data Structure: Linear data structure: Data structure in which data elements are arranged sequentially or linearly, where each element is attached to its previous and next adjacent elements, is called a linear data structure. Examples of linear data structures are array, stack, queue, linked list, etc. Non-linear data structure: Data structures where data elements are not placed sequentially or linearly are called non-linear data structures. In a non-linear data structure, we can’t traverse all the elements in a single run only. Examples of non-linear data structures are trees and graphs.

ii) What is ADT?

The abstract data type is special kind of data type, whose behavior is defined by a set of values and set of operations. The keyword “Abstract” is used as we can use these data types, we can perform different operations. But how those operations are working that is totally hidden from the user. The ADT is made of with primitive data types, but operation logics are hidden. Some examples of ADT are Stack, Queue and List etc. Advantages of ADT: Provides abstraction, which simplifies the complexity of the data structure and allows users to focus on the functionality. Allow users to work with data structures without having to know the implementation details, which can simplify programming and reduce errors

iii)List varius types of asymptotic notations.

There are mainly three asymptotic notations:

  1. Big-O Notation (O-notation)
  2. Omega Notation (Ω-notation)
  3. Theta Notation (Θ-notation) Theta Notation (Θ-Notation): Theta notation represents the upper and the lower bound of the running time of an algorithm, it is used for analyzing the average-case complexity of an algorithm. Big-O Notation (O-notation): Big-O notation represents the upper bound of the running time of an algorithm. Therefore, it gives the worst-case complexity of an algorithm. Omega Notation (Ω-Notation): Omega notation represents the lower bound of the running time of an algorithm. Thus, it provides the best case complexity of an algorithm.

iv)Define the following tearms.

Data type: Data Type is the kind or form of a variable which is being used throughout the program. It defines that the particular variable will assign the values of the given data type only. Data Object: A data object is a region of storage that contains a value or group of values. Each value can be accessed using its identifier or a more complex expression that refers to the object. In addition, each object has a unique data type. Algorithm: An algorithm is a sequence of steps executed by a computer that takes an input and transforms it into a target output. Time Complexity: Time complexity is a type of computational complexity that describes the time required to execute an algorithm. The time complexity of an algorithm is the amount of time it takes for each statement to complete. Space complexity : Space complexity refers to the total amount of memory space used by an algorithm/program, including the space of input values for execution. Calculate the space occupied by variables in an algorithm/program to determine space complexity.