Introduction to Data Structure and Algorithm

In this article, I am going to give you a brief introduction to Data Structure and Algorithm. At the end of this article, you will understand what is Data Structure and Algorithm, its type, and why we need data structure and algorithm as well as Variables and Data Types.

Variables:
let's take an simple mathematical equation.
x + y – 10 = 20 eq1.1
For now, we don’t need to worry about the equation. As we all can observe, the eq1.1 has some names which hold values(data). Similarly, in programming something required to hold data, and we called them variables. In eq1.1, x & y are variables which holds some data.

Data Types:
In eq1.1, x & y holds some data and the data may be integers or floats like 0,1, 0.5, -6.4 , -2 etc. A data type is a set of some predefined values like Integers, Floating points, character, strings etc. There are two types of data types.

1. System – defined Data types (also called as Primitive data types)
2. User – defined Data types

System Defined Data Types
Primitive data type defined by the system .It is provided by programming language. Example – int, float, char, bool, etc.

Allocation of bits for each primitive data type depends on programming language, operating system, and compiler. Different programming language may allocate different size for the same primitive data type.

User-Defined Data Types
In many cases to solve a problem, system-defined data types are not enough. To overcome this situation many programming languages allow the users to define their own data type called user define data types.

Data Structures in C/C++ and classes in java are good examples. Generally, user-defined data type is a combination of much primitive data type.

struct usrdef {
     int sysdef1;
    float sysdef2;
    bool sysdef3;
};

Data Structure
In computer science, a data structure is a data organization, management, and storage format that enables efficient access and modification. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data.

In simple words, a data structure is a way of storing and organizing data so that it can be used efficiently.

Types of Data Structure:
Data Structure classified mainly into two types.
Linear Data Structure:- A Linear data structure have data elements arranged in a sequential manner and each member element is connected to its previous and next element.
Example:- LinkedList, stacks, queue, trees, graphs, etc.

Non-Linear Data Structures:- A non-linear data structure has no set sequence of connecting all its elements and each element can have multiple paths to connect to other elements.
Example:- Trees, Graphs.

For a better understanding of the classification of data structure please have a look at the following diagram.

Key Differences between Linear and Non-Linear Data Structure

Advantages of Data Structures or why we need Data Structure?
We need data structures, few of them are as follows:

1. They are essential ingredients in creating a fast and powerful algorithm.
2. They help to manage and organize data.
3. They make code cleaner and easier to understand.

Abstract Data Types
Basic operation like addition, multiplication, division, subtraction supported by primitive data type but for the user-defined data type, we need to define operations. such operations can be defined at the time of implementation.

In general, user-defined data types are defined along with their operations. The combination of data structures along with their operations is called Abstract Data Types (ADTs). It mainly consists of two parts.

1. Declaration of data
2. Declaration of operations

What is an Algorithm?
An algorithm is a set of one – by – one instruction to solve a particular problem.

Example:- Adding two numbers given by the users

Step 1: Start
Step 2: Declare variables no1, no2, and summation.
Step 3: Read values no1 and no2 that is provided by the user.
Step 4: Add no1 and no2 and assign the result to summation.
             summation ← num1 + num2
Step 5: Display summation
Step 6: Stop

Properties of a good algorithm

1. Input and output should be clearly defined.
2. Each step in the algorithm should be clear and unambiguous.
3. Algorithms should be most effective among many different ways to solve a problem.

The algorithm should be written in such a way that it can be used in different programming languages. No coding is allowed.

In the next article, I am going to discuss the Analysis of Algorithm in detail. Here, in this article, I try to give a brief introduction to Data Structure and Algorithm and I hope you enjoy this article. I hope you enjoy this Introduction to Data Structure and Algorithm article. I would like to have your feedback. Please post your feedback, question, or comments about this article.

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