DATA STRUCTURES AND ALGORITHM Data is a collection of facts and figures or a set of values or values of a specific format that refers to a single set of item values The data items are then classified into sub items which is the group of items that are not known as the simple primary form of the item Let us consider an example where an employee name can be broken down into three sub items First Middle and Last However an ID assigned to an employee will generally be considered a single item What is Data Structure Data Structure is a branch of Computer Science The study of data structure allows us to understand the organization of data and the management of the data flow in order to increase the efficiency of any process or program Data Structure is a particular way of storing and organizing data in the memory of the computer so that these data can easily be retrieved and efficiently utilized in the future when required The data can be managed in various ways like the logical or mathematical model for a specific organization of data is known as a data structure The scope of a particular data model depends on two factors 1 First it must be loaded enough into the structure to reflect the definite correlation of the data with a 2 Second the formation should be so straightforward that one can adapt to process the data efficiently real world object whenever necessary Some examples of Data Structures are Arrays Linked Lists Stack Queue Trees etc Data Structures are widely used in almost every aspect of Computer Science i e Compiler Design Operating Systems Graphics Artificial Intelligence and many more Data Structures are the main part of many Computer Science Algorithms as they allow the programmers to manage the data in an effective way It plays a crucial role in improving the performance of a program or software as the main objective of the software is to store and retrieve the user s data as fast as possible Basic Terminologies related to Data Structures Data Structures are the building blocks of any software or program Selecting the suitable data structure for a program is an extremely challenging task for a programmer The following are some fundamental terminologies used whenever the data structures are involved 1 Data We can define data as an elementary value or a collection of values For example the Employee s name and ID are the data related to the Employee 2 Data Items A Single unit of value is known as Data Item 3 Group Items Data Items that have subordinate data items are known as Group Items For example an employee s name can have a first middle and last name 4 Elementary Items Data Items that are unable to divide into sub items are known as Elementary Items For example the ID of an Employee 5 Entity and Attribute A class of certain objects is represented by an Entity It consists of different Attributes Each Attribute symbolizes the specific property of that Entity For example Attributes ID Name Gender Job Title Values 1234 Stacey M Hill Female Software Developer Entities with similar attributes form an Entity Set Each attribute of an entity set has a range of values the set of all possible values that could be assigned to the specific attribute The term information is sometimes utilized for data with given attributes of meaningful or processed data 1 Field A single elementary unit of information symbolizing the Attribute of an Entity is known as Field 2 Record A collection of different data items are known as a Record For example if we talk about the employee entity then its name id address and job title can be grouped to form the record for the employee 3 File A collection of different Records of one entity type is known as a File For example if there are 100 employees there will be 25 records in the related file containing data about each employee Understanding the Need for Data Structures As applications are becoming more complex and the amount of data is increasing every day which may lead to problems with data searching processing speed multiple requests handling and many more Data Structures support different methods to organize manage and store data efficiently With the help of Data Structures we can easily traverse the data items Data Structures provide Efficiency Reusability and Abstraction Why should we learn Data Structures 1 Data Structures and Algorithms are two of the key aspects of Computer Science 2 Data Structures allow us to organize and store data whereas Algorithms allow us to process that data meaningfully 3 Learning Data Structures and Algorithms will help us become better Programmers 4 We will be able to write code that is more effective and reliable 5 We will also be able to solve problems more quickly and efficiently Understanding the Objectives of Data Structures Data Structures satisfy two complementary objectives 1 Correctness Data Structures are designed to operate correctly for all kinds of inputs based on the domain of interest In order words correctness forms the primary objective of Data Structure which always depends upon the problems that the Data Structure is meant to solve 2 Efficiency Data Structures also requires to be efficient It should process the data quickly without utilizing many computer resources like memory space In a real time state the efficiency of a data structure is a key factor in determining the success and failure of the process ome of the Significant Features of Data Structures are 1 Robustness Generally all computer programmers aim to produce software that yields correct output for every possible input along with efficient execution on all hardware platforms This type of robust software must manage both valid and invalid inputs 2 Adaptability Building software applications like Web Browsers Word Processors and Internet Search Engine include huge software systems that require correct and efficient working or execution for many years Moreover software evolves due to emerging technologies or ever changing market conditions 3 Reusability The features like Reusability and Adaptability go hand in hand It is known that the programmer needs many resources to build any software making it a costly enterprise However if the software is developed in a reusable and adaptable way then it can be applied in most future applications Thus by executing quality data structures it is possible to build reusable software which appears to be cost effective and timesaving Classification of Data Structures A Data Structure delivers a