Full Stack Developer Interview Questions: A full-stack developer is a web developer or engineer who works with both the front and back ends of a website or application meaning they can tackle projects that involve databases, building user-facing websites, or even work with clients during the planning phase of projects.
Full Stack Developer Interview Questions
What is required of a qualified full-stack developer?
He or she must be proficient in multiple programming languages, frameworks, front-end development languages, databases, and design software.
What is meant by data attributes?
Full Stack Developer Interview Questions: In HTML5, these are custom attributes that are defined by the developer. Normally, they are used when all existing attributes are not suitable for the task at hand. However, their scope is limited to the page they are written on.
What does the acronym ACID stand for in database management systems?
Atomicity, Consistency, Isolation, and Durability.
What is normalization in databases?
It is a process of eliminating data redundancy to save on space and maintain the consistency of data.
What is denormalization?
It is the opposite of normalization. In this process, the user increases data redundancy by avoiding joins. As a result, the performance of the database is improved.
Explain the difference between horizontal scaling and vertical scaling?
Full Stack Developer Interview Questions: In horizontal scaling more machines are added to existing resources. As a result, there is no limit to extensibility. In vertical scaling more resources like RAM and the power of the CPU are added; extensibility depends on the capacity of the machine.
How are they used?
They are used to define the methods and properties of all objects that are inherited from the parent object.
What are the differences between constructors and deconstructors
- A constructor allocates memory to an object while a destructor deallocates memory from objects.
- Constructors accept arguments while destructors do not.
What is Node.js
What is Python’s full-stack?
Full Stack Python Developer Python is a versatile all-purpose high-level language that is used for scientific data and other structured as well as unstructured data. A full–stack Python Does the developer have expertise in using Python a suite of languages for all the applications.
Is DevOps part of full-stack?
‘Full–Stack‘ and ‘DevOps‘ are both terms that blur the lines between developer and engineer, and both are two sides of an intriguing form of cross-pollination; technologies more commonly used for deployment and automation.
What is the core difference between REST and GraphQL?
The most fundamental difference between REST and GraphQL is that in the REST model, the type/shape of the resource and the way of retrieving that resource is coupled, whereas in GraphQL these two concepts are completely independent of each other. Basically, the core difference between the two is that in GraphQL, the description of a particular resource is not coupled to the way of retrieving it, unlike REST.
Name a few ways in which you could optimize a website to enhance its scalability and efficiency.
A Full Stack Developer can optimize a website in the by:
- Reducing DNS lookups.
- Avoid URL redirects.
- Avoiding duplicate codes.
- Avoiding unnecessary images.
- Leveraging browser caching.
- Using srcset for responsive images.
- Placing all assets on a cookie-free domain, preferably using a CDN.
What is CORS?
CORS stands for Cross-Origin Resource Sharing. It is a technique used for accessing web resources on diverse domains. CORS allows you to seamlessly integrate web scripts with the external content of the primary domain, thereby facilitating better web service integration.
INTRODUCTION TO PROGRAMMING
a. Program Structure & Basic Principles
b. Programming Constructs – Loops, Functions, Arrays, Etc.
c. An Introduction to Version Control, Git, Command-line Scripting
d. Basic HTML, CSS
BACK END SOFTWARE DEVELOPMENT
• Object-Oriented Paradigms of Java Programming (Classes, Objects etc.)
• Object-Oriented Design
• Exception Handling, Collections, Concurrency, etc.
• Linear Data Structures (Arrays, Strings, Stacks, Queues, Linked Lists, etc.)
• Binary Trees and Binary Search Trees, Tree traversals
• Basic Algorithms: Recursion, Searching and Sorting Algorithms,
• Analysis of Algorithms and Evaluating the right algorithm for a problem
• Self Study: Advanced algorithms – Graphs, Dynamic Programming,
DATABASE DESIGN & SYSTEMS
• Processing, Storing & Organizing Data: Data Models,
• Tables, Views, SQL Queries – Simple & Complex
• Database Schemas, Normalization, Keys, Indexes
• Introduction to NoSQL databases
SERVER-SIDE DEVELOPMENT & FRAMEWORKS
• Spring MVC Architecture
• Backend Development Using Springboot Framework
• ORM & Hibernate
• REST APIs
FRONT END SOFTWARE DEVELOPMENT
FRONT-END DEVELOPMENT – HTML & CSS
• HTML & CSS Interaction, CSS : Styling, Selectors, Box Model, Border, Margin, padding, etc
Server, Event Listeners, Local and Session Storage, etc.
Destructuring, Async/Await, Babel, Webpack, etc
• React Introduction, React Router, Components, and Single Page Applications
• React Forms, Flow Architecture
• Redux & Client-Server Communication, etc
SPECIALIZATION IN CLOUD COMPUTING
• Linux OS
• File Structure
• Command-Line Ops
• Linux Distros & Usage
• Basic Shell Scripting
• Language Basics
• Python Scripting
• Using AWS Python SDK
• Service Models
• Deployment Models
• Virtual Machines vs Containers
• Why Cloud
• Traditional vs Cloud Infra
• Cloud Platforms
• Container Basics
• System Containers (LXD)
• Application Containers (Docker)
• Container Orchestration & Management
COURSE – SPECIALIZATION IN CLOUD COMPUTING
• AWS Organization & IAM
• Database Services (RDS, DynamoDB)
• PaaS – Elastic BeanStalk
• CaaS – Elastic Container Service
• Monitoring & Logging – AWS CloudWatch, CloudTrail
• Notifications – SNS, SES
• Billing & Account Management
DEVOPS ON AWS
• Continuous Integration and Continuous Deployment
• Deployment Pipeline(e.g. AWS CodePipeline, CodeCommit, CodeBuild, CodeDeploy)
• Plan, Build, Deploy and Monitor (CloudFormation)
• Infrastructure as Code (Terraform, CloudFormation)
SPECIALIZATION IN PYTHON FOR DATA SCIENCE
PYTHON FOR DATA SCIENCE
• Introduction to DBMS
• Subqueries and Joins
• Functions, Operations, Grouping & Filtering, etc.
EXPLORATORY DATA ANALYSIS
• Data Cleaning
• Data Preprocessing
• Feature Engineering
• Predictive Modelling- Linear Regression
COURSE – SPECIALIZATION IN PYTHON FOR DATA SCIENCE TOOLS COVERED
• Predictive modelling- Logistic Regression
• Popular supervised ML Algorithms
• Naive Bayes
• K-Nearest Neighbor
• Decision Tree
• Introduction to Clustering
• K Means Clustering
• Silhouette coffecient for K means
• Visual Analysis of clustering
APPLICATIONS (SELF PACED OPTIONAL CONTENT)
• Time Series
• Text Mining