Data Structures and Algorithms (DSA) Introduction

   Last Updated: 08 October, 2024       🕓  3 Mins Read

What is Data Structure?

A data structure is a way of organizing, managing, and storing data in a computer so that it can be accessed and modified efficiently. It defines the relationships between data and how they can be operated on. Data structures are essential for writing efficient algorithms and handling large amounts of data.

Classification of Data Structure:

There are various types of data structures, each suited for different kinds of operations and applications.

Data structure is mainly classified into two categories:

1. Linear Data Structure
2. Non-Linear Data Structure

What is Linear data structure?

A linear data structure arranges data elements sequentially or linearly, connecting each element to its preceding and subsequent adjacent elements.

Examples of linear data structures are Arrays, Stacks, Queues, Linked Lists, etc.

Linear data structures are further divided into two distinct categories: static and dynamic data structures.

• Static Data Structure: A static data structure has a fixed memory size. The elements of a static data structure are simpler to retrieve. An array is an example of a static data structure.

• Dynamic Data Structure: In dynamic data structure, the memory size is not fixed it can be changed during the runtime, which may be considered efficient concerning the memory (space) complexity of the code. Examples of this data structure are queue, stack, etc.

What is Non-Linear Data Structure?

Non-linear data structures are those whose elements are not arranged sequentially or linearly. Instead, elements are organized in a hierarchical or interconnected manner, forming complex relationships between elements.

Non-linear data structures offer greater flexibility and efficiency for organizing relationships and hierarchical data.

Trees and Graphs are the popular examples of non-linear data structures.

What is an Algorithm?

An algorithm is defined as a set of instructions for solving a problem or accomplishing a task. Algorithms are used in many different industries and have many applications. The fields of computer science, mathematics, operations research, artificial intelligence, data science, etc. are some of the major ones that use algorithms.

For complicated issues to be solved successfully and efficiently, algorithms are required.

Specifications of Algorithms

Every algorithm must satisfy the following characteristics:

1. Input - Every algorithm must take zero or more number of input values from external.
2. Output - Every algorithm must produce an output as result.
3. Definiteness - Every statement/instruction in an algorithm must be clear and unambiguous (only one interpretation).
4. Finiteness - For all different cases, the algorithm must produce result within a finite number of steps.
5. Effectiveness - Every instruction must be basic enough to be carried out and it also must be feasible.

Example for an Algorithm

Let us consider the following problem for finding the largest value in a given list of values.

Problem Statement : Find the largest number in the given list of numbers?

Input : A list of positive integer numbers. (List must contain at least one number).

Output : The largest number in the given list of positive integer numbers.

Consider the given list of numbers as 'L' (input), and the largest number as 'max' (Output).

Algorithm

1. Step 1: Define a variable 'max' and initialize with '0'.
2. Step 2: Compare first number (say 'x') in the list 'L' with 'max', if 'x' is larger than 'max', set 'max' to 'x'.
3. Step 3: Repeat step 2 for all numbers in the list 'L'.
4. Step 4: Display the value of 'max' as a result.