Detailed Guide for Software Engineer’s Interview (Backend) -

Topics

OOP (Object Oriented Programming)
Data Structures
Database
Problem Solving

OOP (Object Oriented Programming)

OOP stands for Object-Oriented Programming.
OOP is computer programming model that organizes software around data, and objects.
OOP is faster and easier to execute.
OOP enables the construction of fully reusable apps with less code and faster development times.
Class and Object are main building blocks of OOP, a class is a template for objects, and an object is an instance of a class.

Class Code Example

public class Person
    {
        public string Name { get; set; }        
        public string Gender { get; set; }
        public string ResidenceCity { get; set; }
        public string ResidenceCountry { get; set; }
    }

Object Code Example

static void Main(string[] args)
        {
            Person saif = new Person();
            saif.Gender = "Male";
            saif.Name = "Saifullah Hakro";
            saif.ResidenceCity = "Karachi";
            saif.ResidenceCountry = "Pakistan";
        }

Pillars of OOP

1.Abstraction

Hiding any unnecessary implementation code.
This concept can help developers more easily make additional changes or additions over time.
In OOP, abstraction is achieved through the use of abstract classes and interfaces.
Focusing on the essential features and ignoring unnecessary details.
It is the process of reducing complex systems to a set of simplified and generalized concepts that can be easily understood and manipulated.

2. Inheritance

A subclass can acquire properties of base class.
Base class contains essential properties and derived class extends its functionality by implementing more methods and incorporating more data members.
This increases reusability of code and helps in more through data and comprehensive analysis of code.
It ensures high level of accuracy

Example Code:

public class School
    {
        public virtual void PrintArea()
        {
            Console.WriteLine("base area");
        }
    }

    public class BeachonHouse: School
    {      
        public override void PrintArea()
        {
            Console.WriteLine("Beachon House School");
        }
    }
}

3. Polymorphism

Poly means many and morph means forms.
It occurs when we have many classes that are related to each other by inheritance.
One object can take many forms.
Reduces the need of duplicate code.
There can be multiple child classes of base class each implementing a specific function in their unique way.

Example Code:

public class School
    {
        public virtual void PrintArea()
        {
            Console.WriteLine("base area");
        }
    }

    public class BeachonHouse: School
    {      
        public override void PrintArea()
        {
            Console.WriteLine("Beachon House School");
        }
    }

    public class DHASchool : School
    {
        public override void PrintArea()
        {
            Console.WriteLine("DHA School");
        }
    }

4. Encapsulation

Make sure that “sensitive” data is hidden from users.
All important information is contained inside an object and only selected information is exposed.
Access modifiers are used for this purpose.
Setter Getter Functionality is used for this purpose.
Encapsule means function and data bound together.

Code Example:

public class Car
    {
        private string Model;

        public Car()
        {
            Model = string.Empty;
        }

        public void setModel(string model)
        {
            this.Model = model;
        }

        public string getModel()
        {
            return this.Model;  
        }
    }

Data Structures

Definition: A storage that is used to store and arrange data is called a data structure.
It is a method of setting up data on a computer to make it easily accessible and up to date.
It is also used for processing, retrieving, and storing data.

Image Showing Different types of Data Structures:

Array

A group of items kept in consecutive memory regions is known as an array.
The goal is to group objects of the same category for storage.
As a result, it is simpler to determine each element’s position by simply adding an offset to a base value, or the address in memory where the array’s first element is stored (generally denoted by the name of the array).

2. Queue

In computer science, a queue is a data structure that represents a sequence of elements in which the addition of new elements takes place at one end, known as the “rear” or “tail,” and the removal of existing elements takes place at the other end, known as the “front” or “head.”
This is a first-in, first-out (FIFO) data structure, which means that the first element added to the queue will be the first one to be removed.
Queues are often used in computer programs to manage and control access to shared resources, such as CPUs, memory, and input/output devices. For example, when multiple processes or threads are competing for access to a shared resource, a queue can be used to ensure that each process or thread gets access in turn, in the order that they requested it.
In programming languages, queues can be implemented using arrays, linked lists, or other data structures.
Standard operations on queues include adding an element to the rear of the queue (enqueue), removing an element from the front of the queue (dequeue), and checking whether the queue is empty.
Queues can also be implemented with additional operations, such as peeking at the front element without removing it, or resizing the queue dynamically.

3. Stack

In computer science, a stack is a linear data structure that follows the Last-In-First-Out (LIFO) principle. It is a collection of elements, with two main operations: push, which adds an element to the top of the stack, and pop, which removes the top element from the stack.
A stack can be thought of as a pile of books, where new books are placed on top of the pile, and books are removed from the top of the pile. The element at the top of the stack is called the top or the head of the stack.
Stacks are used in a variety of computer applications, such as compilers, operating systems, and network protocols. They are often used to keep track of the execution of a program, for example, to keep track of function calls and their parameters. Stacks are also used in memory management, where they are used to store data for temporary use.
Stacks can be implemented using arrays or linked lists. In an array-based implementation, a fixed-size array is used to store the stack elements, and a variable called “top” keeps track of the index of the top element. In a linked-list based implementation, each element in the stack is represented by a node that contains the element and a reference to the next node in the stack.

4. LinkedList

In computer science, a linked list is a linear data structure in which elements are stored as nodes, each containing a value and a reference to the next node in the list. The first node is called the head, and the last node is called the tail, which points to a null reference.
Linked lists can be used to implement various abstract data types, such as stacks, queues, and associative arrays. They have several advantages over arrays, including dynamic size, efficient insertion and deletion of elements, and easy implementation of advanced data structures.
There are two main types of linked lists: singly linked lists and doubly linked lists. In a singly linked list, each node contains a reference to the next node in the list. In a doubly linked list, each node contains references to both the next and previous nodes in the list, allowing for traversal in both directions.
Linked lists have several standard operations, including adding elements to the list (insertion), removing elements from the list (deletion), searching for elements in the list, and traversing the list. In addition, several advanced operations can be performed on linked lists, such as sorting and merging two lists.
Linked lists are widely used in programming languages, and are often used in conjunction with other data structures, such as trees and graphs, to create more complex data structures.

Database

A database is a structured collection of data that is stored and organized in a way that allows for efficient retrieval, management, and modification of data. It is a central repository of data that can be accessed and manipulated by various users and applications.
A database typically consists of tables, which contain rows and columns of data. Each row represents a single record or instance, and each column represents a specific attribute or field of the record. For example, a database for a retail store may have tables for customers, products, orders, and sales, each with its own set of attributes.
Databases can be classified into various types based on their organization and structure. The most common types are relational databases, where data is organized into tables with predefined relationships between them, and NoSQL databases, which use a more flexible data model and do not rely on predefined relationships between data.
Databases are used in a wide range of applications, including business, finance, healthcare, education, and scientific research. They are essential for storing and managing large volumes of data, and for ensuring the accuracy, consistency, and security of the data.
Database management systems (DBMS) are software tools that are used to create, manage, and maintain databases. Examples of popular DBMSs include Oracle, MySQL, Microsoft SQL Server, PostgreSQL, and MongoDB.

Problem Solving

Problem-solving in computer science is the process of finding solutions to computational problems using algorithms, data structures, and computational thinking. It involves identifying a problem, analyzing the problem, developing a solution, and testing the solution to ensure that it is correct and efficient.
The first step in problem-solving is identifying the problem or task that needs to be accomplished. This involves understanding the problem statement, the input data, and the expected output.
The next step is analyzing the problem to determine the best approach for solving it. This involves breaking down the problem into smaller subproblems, identifying the appropriate data structures and algorithms to use, and considering factors such as time complexity, space complexity, and scalability.
Once a solution has been developed, it needs to be implemented and tested to ensure that it is correct and efficient. This involves coding the solution, testing it with various input data and edge cases, and optimizing the solution if necessary.
Problem-solving in computer science is a crucial skill for software developers, data scientists, and other professionals working in the field of computer science. It requires a combination of analytical, logical, and creative thinking skills, as well as knowledge of programming languages, data structures, and algorithms.

How to enhance problem solving skills?

Here are some tips for enhancing problem-solving skills in computer science:

Practice, Practice, Practice: The more problems you solve, the better you will become at problem-solving. Practice solving problems on a regular basis, and challenge yourself to tackle more complex problems over time.
Break Down Problems: When faced with a complex problem, break it down into smaller, more manageable sub-problems. This will make the problem easier to solve and help you avoid feeling overwhelmed.
Develop a Systematic Approach: Develop a systematic approach to problem-solving that works for you. This might involve using pseudocode, drawing diagrams, or creating test cases to help you think through the problem.
Learn Data Structures and Algorithms: Familiarize yourself with common data structures and algorithms used in computer science. This will help you identify the best approach for solving a problem and improve your ability to write efficient code.
Collaborate with Others: Collaborating with others on problem-solving can help you learn new techniques and approaches. Participate in coding communities, attend hackathons, and work on open-source projects to learn from others and expand your problem-solving skills.
Read and Learn from Others: Read books, articles, and blogs about problem-solving in computer science. Learn from the experience and insights of other professionals in the field.
Reflect on Your Process: Reflect on your problem-solving process after solving a problem. Consider what worked well and what could be improved, and use this feedback to improve your problem-solving skills over time.

About the Author:

As you are aware, my name is Saifullah Hakro. I completed my BS in Computer Science at FAST NUCES Karachi between 2013 and 2017 with a 3.49 grade point average. I have been a software developer in the software sector since 2017 with a focus on (.NET Domain). I enjoy creating articles and reading books.

Disclaimer:

These ideas come from my experience and research, thus they might not be entirely accurate or flawless.