Data Structure and Algorithm is an amazing tutorial series to learn about different sorting ,searching ,data structures like Time Complexity, Linked List, Queue , Tree, B+ Tree ,and more.


Most frequent questions and answers

The data structure is a way that specifies how to organize and manipulate the data. It also defines the relationship between them. Some examples of Data Structures are arrays, Linked List, Stack, Queue, etc.

An ADT is a mathematical model of a data structure that specifies the type of data stored, the operations supported on them, and the types of parameters of the operations. An ADT specifies what each operation does, but not how it does it. Typically, an ADT can be implemented using one of many different data structures.

They are essential components in creating fast and powerful algorithms. They help to manage and organize data so that it will make our code cleaner and easier to understand. Data structures can make the difference between an Okay product and an outstanding one.

To implement printer spooler so that jobs can be printed in the order of their arrival. To implement back functionality in the internet browser. To store the possible moves in a chess game. To store a set of fixed key words which are referenced very frequently.

In my opinion, C would be the best language to learn data structures and algorithms because it will force you to write your own. It will force you to understand pointers, dynamic memory allocation, and the implementations behind the popular data structures like linked lists, hash tables, etc.

vector is a one-dimensional data structure and all of its elements are of the same data type. A factor is one-dimensional and every element must be one of a fixed set of values, called the levels of the factor.

There are two fundamental kinds of data structures: array of contiguous memory locations and linked structures.

The advantages of queues are that the multiple data can be handled, and they are fast and flexibility, and Disadvantages of queues: To include a new element in the queue, the other elements must be deleted.

In a linear queue, the traversal through the queue is possible only once,i.e.,once an element is deleted, we cannot insert another element in its position. This disadvantage of a linear queue is overcome by a circular queue, thus saving memory.

The dequeue stands for Double Ended Queue. In the queue, the insertion takes place from one end while the deletion takes place from another end. The end at which the insertion occurs is known as the rear end whereas the end at which the deletion occurs is known as front end.

Data Structure Analysis summarizes a program’s memory composition and con- nectivity patterns by building a Data Structure Graph (DS graph) for each available function in the program. Many design features of DS graphs have been carefully chosen to make the analysis very efficient in practice.

An algorithm must have five properties:
  • Input specified.
  • Output specified.
  • Definiteness.
  • Effectiveness.
  • Finiteness.

Big O notation is a mathematical notation that describes the limiting behavior of a function when the argument tends towards a particular value or infinity. In computer science, big O notation is used to classify algorithms according to how their run time or space requirements grow as the input size grows.

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