Please provide your suggestion to make this document very useful.
- You are expecting an interview soon and you want to cover the most of the important topic as early as possible.
- Candidate have some basic computer science fundamental knowledge.
- Speding more than 10 mins on each topic will not be worth if you have tight deadline.
- Need single source of document for an interview, referring multiple website require considrable amount of time and efforts.
- Each topic required some interview questions and answers.
Note:- Clicking on each link will navigate us to detail page which contains source code using C# and problem you may encounter during interview
This Github repository will covers most of the software engineering interview question and answers , also reference for the questions (leetcode, geeksforgeeks,hackerrank,hackerearth, youtupe etc). , any one have good understanding of object oriented programming can able to understand the code. I started documenting all together and provide the single source for an interview preparation. This will not cover 100% interview problem but it will help us to understand all the important topics and it covers some overview of Data Structure and Algorithm, Design Pattern, OOPS, Object Oriented design for a realtime problem, DBMS (SQL and NOSQL), Network, Problem Solving and System Design. I will keep update this repository as I learn. Basic understading of programming language is require to understand the code.
Suggestions and comments are welcome.
Data Structures and Algorithms
Data structure is a particular way of storing and organizing information in a computer so that it can be retrieved and used most productively.
- Data structures are used in almost every program or software system.
- Each Data Structure allows data to be stored in specific manner.
- Data Structure allows efficient data search and retrieval.
- Specific Data structures are decided to work for specific problems.
-
Time complexity of an algorithm quantifies the amount of time taken by an algorithm to run as a function of the length of the input.
-
Space complexity of an algorithm quantifies the amount of space or memory taken by an algorithm to run as a function of the length of the input.
Algorithm complexity is commonly represented with the O(n) notation, - also known as asymptotic notation or “Big O notation”, where n is the function of the size of the input data. We need to know how well our algorithm perform in Best Case, Average Case and Worst Case
Refer:- http://bigocheatsheet.com/
Most interviewers won't ask about specific algorithms for binary tree balancing or other complex algorithms and You're usually only expected to know the basics.
Method to store information
| Data Structure | |
|---|---|
| Array | An array, is a data structure consisting of a collection of elements (values or variables), each identified by at least one array index. |
| Linked List | A linked list is a linear data structure where each element is a separate object. Linked list elements are not stored at contiguous location; the elements are linked using pointers. |
| ArrayList | It is similar to an array, except that it grows automatically as you add items in it. Unlike an array, you don't need to specify the size of ArrayList. |
| Trees | Binary Search Tree, Binary Tree A tree is a collection of nodes connected by directed (or undirected) edges |
| Graph | A graph is a data structure where a node can have zero or more adjacent elements. |
| Stack | Stack is a linear data structure which represents a simple last-in-first-out (LIFO) |
| Queue | Queue is a linear data structure which represents a simple first-in-first-out (FIFO) |
| Heap | A Heap or Binary heap is a complete binary tree which satisfies the heap ordering property. |
| HashTable/Dictionary | A hash table is a data structure that is used to store keys/value pairs, and retrive value by passing key |
Method for solving a problem
| Algorithm | Stable | |
|---|---|---|
| Depth-First-Search | The depth-first algorithm sticks with one path, following that path down a graph structure until it ends | N/A |
| Breadth-First Search | The breadth-first search approach, however, evaluates all the possible paths from a given node equally | N/A |
| Tree Traversal | A traversal is a process that visits all the nodes in the tree. Since a tree is a nonlinear data structure, there is no unique traversal (BFS, Inorder, Postorder, Preorder) | N/A |
| Merge Sort | Divide and Conquer algorithm | Yes |
| Quick Sort | Divide and Conquer algorithm | No |
| Insertion Sort | Yes | |
| Selection Sort | No | |
| Bubble Sort | Yes | |
| Binary Search | O(log(n)) | N/A |
| Dijkstra | Path finding | N/A |
Most of the time we hear the term called Greed and Naive/Brute-force Algorithm
Greed algorithm : Greedy algorithm is one which finds the feasible solution at every stage with the hope of finding global optimum solution.
Brute-force Algorithms : Solves a problem in the most simple, direct, or obvious way.
| Programming Concepts | |
|---|---|
| Dynamic Programming | Dynamic Programming is a method for solving a complex problem by breaking it down into a collection of simpler subproblems, solving each of those subproblems just once, and storing their solutions using a memory. |
| Recursion | When a function calls itself, its called Recursion. Recursion is useful in solving problems which can be broken down into smaller problems of the same kind. |
| Backtracking | In backtracking we can build a solution step by step using recursion; if during the process we realise that is not going to be a valid solution, then we stop computing that solution and we return back to the step before (backtrack) |
| Big O | Algorithm complexity is commonly represented with the O(n) notation, also known as asymptotic notation or “Big O notation”, where n is the function of the size of the input data. |
| Memory | Stack Variables allocated on the stack are stored directly to the memory and access to this memory is very fast, and it's allocation is dealt with when the program is compiled. Heap Variables allocated on the heap have their memory allocated at run time and accessing this memory is a bit slower, but the heap size is only limited by the size of virtual memory. |
- Creational design patterns are used to design the instantiation process of objects. The creational pattern uses the inheritance to vary the object creation
- Structural patterns are concerned with how classes and objects are composed to form larger structures. Structural class patterns use inheritance to compose interfaces or implementations.
- Behavioral patterns are concerned with algorithms and the assignment of responsibilities between objects. Behavioral patterns describe not just patterns of objects or classes but also the patterns of communication between them.
| Creational Patterns | Structural Patterns | Behavioral Patterns |
|---|---|---|
| Abstract Factory | Adapter | Chain of Responsibility |
| Builder | Bridge | Command |
| Factory Method | Composite | Interpreter |
| Prototype | Decorator | Iterator |
| Singleton | Facade | Mediator |
| Flyweight | Memento | |
| Proxy | Observer | |
| State | ||
| Strategy | ||
| Template Method | ||
| Visitor |
A database management system (DBMS) is system software for creating and managing databases. The DBMS provides users and programmers with a systematic way to create, retrieve, update and manage data.
There are many types of database but will consider SQL and NOSQL database.
Distributed computing, a single problem is divided into many parts, and each part is solved by different computers.
A load balancer is a device that acts as a reverse proxy and distributes network or application traffic across a number of servers. Load balancers are used to increase capacity (concurrent users) and reliability of applications. They improve the overall performance of applications by decreasing the burden on servers associated with managing and maintaining application and network sessions, as well as by performing application-specific tasks. Load balancers are generally grouped into two categories: Layer 4 and Layer 7. Layer 4 load balancers act upon data found in network and transport layer protocols (IP, TCP, FTP, UDP). Layer 7 load balancers distribute requests based upon data found in application layer protocols such as HTTP.
- TCP/IP (Transmission Control Protocol/Internet Protocol)
- ARP (Address Resolution Protocol)
- DHCP (Dynamic Host Configuration Protocol)
- DNS (Domain Name System)
- FTP (File Transfer Protocol)
- SMTP (Simple mail transport Protocol)
- HTTP
- UDP
TCP (Transmission Control Protocol) is connection oriented, whereas UDP (User Datagram Protocol) is connection-less. This means that TCP tracks all data sent, requiring acknowledgment for each octet (generally). UDP does not use acknowledgments at all, and is usually used for protocols where a few lost datagrams do not matter. Because of acknowledgments, TCP is considered a reliable data transfer protocol. It ensures that no data is sent to the upper layer application that is out of order, duplicated, or has missing pieces. It can even manage transmissions to attempt to reduce congestion
The primary uses for UDP include service advertisements, such as routing protocol updates
and server availability, one-to-many multicast applications, and streaming applications,
such as voice and video, where a lost datagram is far less important than an out-of-order datagram.*
- Application Load Balancer
- HTTP/HTTPS
- Network Load Balancer
- TCP/SSL
- Classic Load Balancer
- Transport layer (TCP/SSL) or the application layer (HTTP/HTTPS)
- Round robin
- Weighted round robin
- Least connections
- Least response time
- IP Hash
- Open the browser and type the URL
- Browser contacts the DNS server via ISP to find the IP address of URL.
- DNS returns back the IP address of the site.
- Browser opens TCP connection to the web server.
- Browser fetches the html code of the page requested.
- Browser renders the HTML in the display window.
- Browser terminates the connection when window is closed.
Uniform Resource Locator (URL) "https://google.com/
Every machine on the Internet has a unique identifying number, called an IP Address. The IP stands for Internet Protocol, which is the language that computers use to communicate over the Internet.
Internet servers make the Internet possible. All of the machines on the Internet are either servers or clients. The machines that provide services to other machines are servers. And the machines that are used to connect to those services are clients.
SOA means that you structure your application by decomposing it into multiple services (most commonly as HTTP services) that can be classified as different types like subsystems or tiers.
Microservice-based software architectures are actually just modernized implementations of the SOA model.
The software components are developed as services to be exposed via APIs, as SOA would require. An API
broker mediates access to components and ensures security and governance practices are followed.
Service-Oriented Architecture (SOA) is an architectural approach in which applications make use of services available in the network.
- Service provider: The service provider is the maintainer of the service and the organization that makes available one or more services for others to use. To advertise services, the provider can publish them in a registry, together with a service contract that specifies the nature of the service, how to use it, the requirements for the service, and the fees charged.
- Service consumer: The service consumer can locate the service metadata in the registry and develop the required client components to bind and use the service.
- Standardized service contract: Specified through one or more service description documents.
- Loose coupling: Services are designed as self-contained components, maintain relationships that minimize dependencies on other services.
- Abstraction: A service is completely defined by service contracts and description documents. They hide their logic, which is encapsulated within their implementation.
- Reusability: Designed as components, services can be reused more effectively, thus reducing development time and the associated costs.
- Autonomy: Services have control over the logic they encapsulate and, from a service consumer point of view, there is no need to know about their implementation.
- Discoverability: Services are defined by description documents that constitute supplemental metadata through which they can be effectively discovered. Service discovery provides an effective means for utilizing third-party resources.
- Composability: Using services as building blocks, sophisticated and complex operations can be implemented. Service orchestration and choreography provide a solid support for composing services and achieving business goals.
• Service reusability: In SOA, applications are made from existing services.Thus, services can be reused to make many applications.
• Easy maintenance: As services are independent of each other they can be updated and modified easily without affecting other services.
• Platform independent: SOA allows making a complex application by combining services picked from different sources, independent of the platform.
• Availability: SOA facilities are easily available to anyone on request.
• Reliability: SOA applications are more reliable because it is easy to debug small services rather than huge codes
• Scalability: Services can run on different servers within an environment, this increases scalability
• High overhead: A validation of input parameters of services is done whenever services interact this decreases performance as it increases load and response time.
• High investment: A huge initial investment is required for SOA.
• Complex service management: When services interact they exchange messages to tasks. The number of messages may go in millions. It becomes a cumbersome task to handle a large number of messages.