DSA - Copy.pptx
- 1. BUDGE BUDGE INSTITUTE OF TECHNOLOGY INTRODUCTION OF DATA STRUCTURE NAME – BISHAL CHOWDHURY ROLL NO - 27600121067 YEAR - 2022 SEMESTER - 3RD SUBJECT CODE - PCC CS-301
- 2. INTRODUCTION A data structure is a group of data elements that provides the easiest way to store and perform different actions on the data of the computer. A data structure is a particular way of organizing data in a computer so that it can be used effectively. Data structures are the building blocks of any program or the software. Choosing the appropriate data structure for a program is the most difficult task for a programmer. Following terminology is used as far as data structures are concerned. • DATA: Data can be defined as an elementary value or the collection of values • Record: Record can be defined as the collection of various data items • File: A File is a collection of various records of one type of entity. • Attribute and Entity: An entity represents the class of certain objects. it contains various attributes. Each attribute represents the particular property of that entity. • Field: Field is a single elementary unit of information representing the attribute of an entity.
- 3. NEED OF DATA STRUCTURES • Processor speed: To handle very large amout of data, high speed processing is required, but as the data is growing day by day to the billions of files per entity, processor may fail to deal with that much amount of data. • Data Search: Consider an inventory size of 106 items in a store, If our application needs to search for a particular item, it needs to traverse 106 items every time, results in slowing down the search process. in order to solve the above problems, data structures are used. Data is organized to form a data structure in such a way that all items are not required to be searched and required data can be searched instantly. As applications are getting complexed and amount of data is increasing day by day, there may arrise the following problems: CLASSIFICATION OF DATA STRUCTURE
- 4. PRIMITIVE DATA STRUCTURE Primitive data structure is a data structure that can hold a single value in a specific location whereas the non-linear data structure can hold multiple values either in a contiguous location or random locations The examples of primitive data structure are float, character, integer and pointer. The value to the primitive data structure is provided by the programmer. The following are the four primitive data structures: •Integer: The integer data type contains the numeric values. It contains the whole numbers that can be either negative or positive. When the range of integer data type is not large enough then in that case, we can use long. •Float: The float is a data type that can hold decimal values. When the precision of decimal value increases then the Double data type is used. •Character: It is a data type that can hold a single character value both uppercase and lowercase such as 'A' or 'a’. NON-PRIMITIVE DATA STRUCTURE The non-primitive data structure is a kind of data structure that can hold multiple values either in a contiguous or random location. The non-primitive data types are defined by the programmer. The non-primitive data structure is further classified into two categories, i.e., linear and non-linear data structure. Array: An array is a data structure that can hold the elements of same type. It cannot contain the elements of different types like integer with character. The commonly used operation in an array is insertion, deletion, traversing, searching
- 5. Linked List: Linked list is a linear data structure which is used to maintain a list in the memory. It can be seen as the collection of nodes stored at non-contiguous memory locations. Each node of the list contains a pointer to its adjacent node. LINEAR DATA STRUCTURE: Data structure where data elements are arranged sequentially or linearly where each and every element is attached to its previous and next adjacent is called a linear data structure. STACK: Stack is a linear list in which insertion and deletions are allowed only at one end, called top. A stack is an abstract data type (ADT), can be implemented in most of the programming languages. It is named as stack because it behaves like a real-world stack, for example: - piles of plates or deck of cards etc. QUEUE: Queue is a linear list in which elements can be inserted only at one end called rear and deleted only at the other end called front. NON LINEAR DATA STRUCTURES: This data structure does not form a sequence i.e. each item or element is connected with two or more other items in a non-linear arrangement. The data elements are not arranged in sequential structure. TREES: Trees are multilevel data structures with a hierarchical relationship among its elements known as nodes. The bottommost nodes in the herierchy are called leaf node while the topmost node is called root node. Each node contains pointers to point adjacent nodes. Graphs: Graphs can be defined as the pictorial representation of the set of elements (represented by vertices) connected by the links known as edges. A graph is different from tree in the sense that a graph can have cycle while the tree can not have the one.
- 6. OPERATIONS ON DATA STRUCTURE: 1) TRAVERSING: Every data structure contains the set of data elements. Traversing the data structure means visiting each element of the data structure in order to perform some specific operation like searching or sorting. Example: If we need to calculate the average of the marks obtained by a student in 6 different subject, we need to traverse the complete array of marks and calculate the total sum, then we will devide that sum by the number of subjects i.e. 6, in order to find the average. 2) INSERTION: Insertion can be defined as the process of adding the elements to the data structure at any location. If the size of data structure is n then we can only insert n-1 data elements into it. 3) DELETION: The process of removing an element from the data structure is called Deletion. We can delete an element from the data structure at any random location. If we try to delete an element from an empty data structure then underflow occurs. 4) SEARCHING: The process of finding the location of an element within the data structure is called Searching. There are two algorithms to perform searching, Linear Search and Binary Search. We will discuss each one of them later in this tutorial. 5) SORTING: The process of arranging the data structure in a specific order is known as Sorting. There are many algorithms that can be used to perform sorting, for example, insertion sort, selection sort, bubble sort, etc. 6) MERGING: When two lists List A and List B of size M and N respectively, of similar type of elements, clubbed or joined to produce the third list, List C of size (M+N), then this process is called merging
- 7. CONCLUSIONS DATA STRUCTURE IS USEFULL IN DAY TO DAY LIFE AND ARE USING THEM MORE FREQUENTLY THAT IS WHY IT IS SO HOT SUBJECT IN INFORMATION TECHNOLOGY INDUSTRY.
- 8. REFERENCE DATA STRUCTURES BY G A VIJAYALAKSHMI PAI