Data structure and Algorithm-learntut

 

Data Structures (DS) tutorial provides basic and advanced concepts of Data Structure. Our Data Structure tutorial is designed for beginners and professionals.

Data Structure is a way to store and organize data so that it can be used efficiently.

Our Data Structure tutorial includes all topics of Data Structure such as Array, Pointer, Structure, Linked List, Stack, Queue, Graph, Searching, Sorting, Programs, etc.

 

Introduction to Data Structures

A data structure is a model where data is organized, managed and stored in a format that enables efficient access and modification of data. There are various types of data structures commonly available. It is up to the programmer to choose which data structure to use depending on the data.

The choice of a particular one can be considered based on the following points:

1. It must be able to process the data efficiently when necessary.
2. It must be able to represent the inherent relationship of the data in the real world.

 

 

Types of Data Structures

There are two types of data structures:

• Primitive data structure
• Non-primitive data structure

 

 

Primitive Data structure

The primitive data structures are primitive data types. The int, char, float, double, and pointer are the primitive data structures that can hold a single value.

 

 

Non-Primitive Data structure

The non-primitive data structure is divided into two types:

• Linear data structure
• Non-linear data structure

 

Linear Data Structure

The arrangement of data in a sequential manner is known as a linear data structure. The data structures used for this purpose are Arrays, Linked list, Stacks, and Queues. In these data structures, one element is connected to only one another element in a linear form.

 

When one element is connected to the 'n' number of elements known as a non-linear data structure. The best example is trees and graphs. In this case, the elements are arranged in a random manner.

 

We will discuss the above data structures in brief in the coming topics. Now, we will see the common operations that we can perform on these data structures.

 

Data structures can also be classified as:

• Static data structure: It is a type of data structure where the size is allocated at the compile time. Therefore, the maximum size is fixed.
• Dynamic data structure: It is a type of data structure where the size is allocated at the run time. Therefore, the maximum size is flexible.

 

Major Operations

The major or the common operations that can be performed on the data structures are:

• Searching: search for any element in a data structure.
• Sorting: sort the elements of a data structure either in an ascending or descending order.
• Insertion: insert the new element in a data structure.
• Update: update the element, i.e., we can replace the element with another element.
• Deletion: the delete operation to remove the element from the data structure.

 

Advantages of Data structures

The following are the advantages of a data structure:

• Efficiency: the choice of a data structure for implementing a particular ADT is proper, it makes the program very efficient in terms of time and space.
• Reusability: he data structures provide reusability means that multiple client programs can use the data structure.
• Abstraction: The data structure specified by an ADT also provides the level of abstraction. The client cannot see the internal working of the data structure, so it does not have to worry about the implementation part. The client can only see the interface.

Basic Terminology

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, for example, student's name and its id are the data about the student.

 

Group Items: Data items which have subordinate data items are called Group item, for example, name of a student can have first name and the last name.

 

Record: Record can be defined as the collection of various data items, for example, if we talk about the student entity, then its name, address, course and marks can be grouped together to form the record for the student.

 

File: A File is a collection of various records of one type of entity, for example, if there are 60 employees in the class, then there will be 20 records in the related file where each record contains the data about each employee.

 

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.

 

Data structure classification

Linear Data Structures: A data structure is called linear if all of its elements are arranged in the linear order. The elements are stored in non-hierarchical way where each element has the successors and predecessors except the first and last element.

Types of Linear Data Structures

Arrays: An array is a collection of similar type of data items and each data item is called an element of the array. The data type of the element may be any valid data type like char, int, float or double.

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.

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.

It is an abstract data structure, similar to stack. Queue is opened at both ends therefore it follows First-In-First-Out (FIFO) methodology for storing the data items.

 

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.

 

Types of Non-Linear Data Structures

 

Trees: Trees are multilevel data structures with a hierarchical relationship among its elements known as nodes. The bottommost nodes in the hierarchy are called leaf node while the topmost node is called root node. Each node contains pointers to point adjacent nodes.

Tree data structure is based on the parent-child relationship among the 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 cannot have the one.

 

Hash Tables: A Hash Table is a data structure where data is stored in an associative manner. The data is mapped to array positions by a hash function that generates a unique value from each key. The value stored in a hash table can then be searched in O (1) time using the same hash function which generates an address from the key.

 Operations on data structure

1) Traversing: Traversing the data structure means visiting each element of the data structure in order to perform some specific operation like searching or sorting.

 

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.

NOTE: If we try to delete an element from 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 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 P and Q respectively, of similar type of elements, joined to produce the third list, List C of size (P+Q), then this process is called merging.