Hire Full-Stack Developers with HackerEarth: Full Guide

Fullstack development roles became prominent around the early to mid-2010s. This emergence was largely driven by several factors, including the rapid evolution of web technologies, the increasing complexity of web applications, and the demand for more versatile developers capable of handling both client-side and server-side programming.

With the rise of powerful frameworks like MEAN, MERN, Django/Flask, RoR, Spring Boot and Angular/React/Vue building powerful web applications has become easier and Fullstack developers have become one of the most critical members of tech teams.

The role has consistently seen an increase in demand. According to the Bureau of Labor Statistics, the demand for web developers, including fullstack professionals, is projected to grow by 13% from 2020 to 2030, faster than the average for all occupations.

Because fullstack development spans across a broad spectrum of skills it's not straightforward to assess these skills. Furthermore, each position requires a unique blend of skills and experience. It's important to look beyond the label and assess their specific strengths in both front-end and back-end technologies, along with their overall understanding of the development process. Additionally, consider tailoring assessments to the specific role and the candidate's skillset for the most accurate evaluation.

Since we launched full-stack questions as part of our question library in 2022, we have added different question types to our library to cover all types of full-stack assessments. At the time of writing this, our library consists of 220+ full-stack questions divided into various types.

In this guide, let’s take a look at the different types of question types for full-stack assessments available on HackerEarth, and how they can help your tech recruiting team in assessing candidates better.

Read More: How to Hire Full Stack Developers

Full-stack question types available on HackerEarth

Here's a detailed breakdown of the available question types on HackerEarth for full-stack assessments, including their purpose, example questions, and how tech recruiting teams can utilize them.

Real-world Problems
- Purpose: This type assesses a candidate's problem-solving approach in realistic scenarios faced by full-stack developers on the job. It evaluates their ability to analyze, understand, and implement solutions considering real-world complexities.
- Example Questions:
  1. A company's e-commerce website experiences a sudden surge in traffic, causing performance issues. How would you diagnose and optimize the site for scalability?
  2. A user reports encountering inconsistencies when switching between the mobile and desktop versions of your application. How would you approach debugging and resolving this issue?
- Use for Recruiters: Real-world problems provide valuable insights into a candidate's thought process, technical skills application, and ability to adapt to practical situations. These questions can help identify candidates who can hit the ground running and contribute meaningfully from day one.
Short Task-Based Questions
- Purpose: This format allows candidates to showcase their expertise in specific tasks within a limited timeframe. It helps gauge their ability to focus, prioritize, and deliver results under pressure.
- Example Questions:
  1. Write a JavaScript function to validate a user's email address format.
  2. Implement a basic API endpoint in Python that returns a list of products from a database.
  3. Design a responsive layout for a product page using HTML and CSS.
- Use for Recruiters: Short task-based questions are ideal for evaluating core technical skills in various areas like front-end development, back-end development, and scripting languages. They offer a quick assessment of a candidate's competency in specific areas relevant to the role.
Debugging Questions
- Purpose: This type tests a candidate's ability to identify, diagnose, and fix errors within code snippets or applications. It assesses their understanding of common coding issues, debugging techniques, and problem-solving skills.
- Example Questions:
  1. A provided Python script throws an error when attempting to access a list element. Why is this happening, and how can it be fixed?
  2. An HTML page displays layout issues in different browsers. What could be causing this, and how would you debug the problem?
- Use for Recruiters: Debugging questions are crucial for evaluating a candidate's ability to identify and resolve technical issues in existing code. This skill is essential for full-stack developers, as they often need to maintain and troubleshoot code written by themselves or others.
Project-Level Full-Stack Questions
- Purpose: This format requires candidates to build end-to-end projects using specific technology stacks. It provides the most comprehensive assessment of a candidate's full-stack development skills, covering front-end, back-end, database interaction, and overall project structure.
- Example: Build a simple to-do list application using a chosen technology stack (e.g., ReactJS, NodeJS, MongoDB). The application should allow users to add, edit, and delete tasks.
- Use for Recruiters: Project-level full-stack questions provide an in-depth evaluation of a candidate's ability to plan, develop, and deploy a complete application. This format is ideal for senior roles where full-stack mastery is essential. However, it can also be used for junior positions to assess their learning potential and ability to apply acquired skills in a practical project.

Features supported by the HackerEarth full-stack question types

Some of the more helpful features that we support include, but are not limited to the following:

Microservices support	The platform supports microservices. The purpose of this is to ensure that candidates can be assessed with technologies that are aligned with industry advancements.
Tech and testing framework diversity	The platform supports a diverse range of technologies, frameworks and testing frameworks that are compatible with various programming languages and methodologies.
Multiple server options	The platform supports multiple server options for hosting services concurrently. We specifically support Jetty servers. This feature allows candidates to select an environment that aligns seamlessly with their specific hosting needs thus enhancing overall adaptability.
Database flexibility	The platform supports a variety of databases, including MySQL, MSSQL, SQLite, and MongoDB. This feature allows admins to create Full stack questions that involve database interactions thus enabling candidates to demonstrate their skills in working with different database systems.
Tags	All the questions in our library are tagged using content-specific tags that can be used to search for questions easily. You can search for a question that can be used to assess specific capabilities within a skill/topic. For example, ngClass, Routing in React, Backend API, REST-API, etc.

Building a well-rounded full-stack assessment with HackerEarth

Crafting an effective full-stack assessment on HackerEarth requires a strategic mix of different question types. Here are few pointers that can help you in utilizing each format and building a well-rounded evaluation:

Start with the core:

Employ short task-based questions to assess fundamental competencies in front-end (HTML, CSS, JavaScript), back-end (Python, Java, etc.), and scripting languages. Use debugging questions to gauge a candidate's problem-solving approach and ability to identify and fix errors in code.
Dig deeper with real-world challenges:

Introduce real-world problems to evaluate a candidate's ability to think critically, analyze complex scenarios, and translate technical skills into solutions for practical situations.
Evaluate application building skills:

Consider project-level full-stack questions for senior roles. These allow candidates to showcase their ability to plan, develop, and deploy a complete application using a specific technology stack. Alternatively, for junior roles, consider a simplified project that assesses their learning potential and ability to apply acquired skills in a practical context.
Tailoring the mix:

Prioritize questions that align with the specific skills required for the role. For example, a front-end heavy position might involve more HTML/CSS questions, while a back-end focused role would emphasize server-side technologies and database interaction.
Adjust assessment level according to candidate experience:

Adjust the complexity of questions based on the experience level you're targeting. Junior developers might benefit from more fundamental tasks, while senior roles can handle in-depth projects and real-world challenges.

Additional tips for crafting a take-home full-stack assessment

Balance theory and practical skills: Combine knowledge-based questions with tasks that require applying those skills in a practical scenario.
Provide clear instructions and time limits: Provide clear instructions and set realistic time limits for each question type.
Keep an eye on the assessment length: Consider the total assessment duration to avoid overwhelming candidates.
Have a transparent evaluation criteria: Establish clear evaluation criteria for each question type to ensure consistent scoring.
Use a mix of predefined vs. custom questions: Utilize HackerEarth's question library alongside custom-crafted scenarios specific to your company's needs.

A strategic combination of these question types, tailored to the specific role and candidate experience, can help you create a full-stack assessment that effectively evaluates the skills and capabilities of potential hires. This will help you identify developers who not only possess the technical expertise but also have the critical thinking and problem-solving skills to thrive in your organization.

Hire your next full-stack developer with HackerEarth!

Earlier this year, the full-stack question usage on our platform went up by 10x. This surge reflects the growing demand for versatile full-stack developers who can manage all aspects of web and application development. The increased adoption of HackerEarth's full-stack assessments likely stems from several factors. Perhaps companies are recognizing the limitations of traditional hiring methods and seeking a more comprehensive evaluation of a candidate's skills. Maybe they're appreciating the ability to tailor assessments to specific roles and company needs. Whatever the reason, we are glad that more and more companies are recognizing the need for customized full-stack assessments and how HackerEarth can be a powerful aid for full-stack developer recruitment.

Are you ready to find your next top full-stack developer with HackerEarth? Explore our extensive library of pre-built questions, customizable assessment options, and AI-powered insights that make finding your ideal full-stack talent a breeze.

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Hackathons

Vibe Coding: Shaping the Future of Software

A New Era of CodeVibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today,...

A New Era of Code

Vibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today, when code is produced quickly through AI, the true value lies in designing, refining, and optimizing systems. Our role now goes beyond writing code; we must also ensure that our systems remain efficient and reliable.

From Machine Language to Natural Language

I recall the early days when every line of code was written manually. We progressed from machine language to high-level programming, and now we are beginning to interact with our tools using natural language. This development does not only increase speed but also changes how we approach problem solving. Product managers can now create working demos in hours instead of weeks, and founders have a clearer way of pitching their ideas with functional prototypes. It is important for us to rethink our role as developers and focus on architecture and system design rather than simply on typing code.

The Promise and the Pitfalls

I have experienced both sides of vibe coding. In cases where the goal was to build a quick prototype or a simple internal tool, AI-generated code provided impressive results. Teams have been able to test new ideas and validate concepts much faster. However, when it comes to more complex systems that require careful planning and attention to detail, the output from AI can be problematic. I have seen situations where AI produces large volumes of code that become difficult to manage without significant human intervention.

AI-powered coding tools like GitHub Copilot and AWS’s Q Developer have demonstrated significant productivity gains. For instance, at the National Australia Bank, it’s reported that half of the production code is generated by Q Developer, allowing developers to focus on higher-level problem-solving . Similarly, platforms like Lovable enable non-coders to build viable tech businesses using natural language prompts, contributing to a shift where AI-generated code reduces the need for large engineering teams. However, there are challenges. AI-generated code can sometimes be verbose or lack the architectural discipline required for complex systems. While AI can rapidly produce prototypes or simple utilities, building large-scale systems still necessitates experienced engineers to refine and optimize the code.

The Economic Impact

The democratization of code generation is altering the economic landscape of software development. As AI tools become more prevalent, the value of average coding skills may diminish, potentially affecting salaries for entry-level positions. Conversely, developers who excel in system design, architecture, and optimization are likely to see increased demand and compensation.
Seizing the Opportunity

Vibe coding is most beneficial in areas such as rapid prototyping and building simple applications or internal tools. It frees up valuable time that we can then invest in higher-level tasks such as system architecture, security, and user experience. When used in the right context, AI becomes a helpful partner that accelerates the development process without replacing the need for skilled engineers.

This is revolutionizing our craft, much like the shift from machine language to assembly to high-level languages did in the past. AI can churn out code at lightning speed, but remember, “Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” Use AI for rapid prototyping, but it’s your expertise that transforms raw output into robust, scalable software. By honing our skills in design and architecture, we ensure our work remains impactful and enduring. Let’s continue to learn, adapt, and build software that stands the test of time.

Ready to streamline your recruitment process? Get a free demo to explore cutting-edge solutions and resources for your hiring needs.

Tech Assessment

Guide to Conducting Successful System Design Interviews in 2025

What is Systems Design?Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.Systems Design, in its...

What is Systems Design?

Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.

Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.

Systems Design, in its essence, is a blueprint of how software and applications should work to meet specific goals. The multi-dimensional nature of this discipline makes it open-ended – as there is no single one-size-fits-all solution to a system design problem.

What is a System Design Interview?

Conducting a System Design interview requires recruiters to take an unconventional approach and look beyond right or wrong answers. Recruiters should aim for evaluating a candidate’s ‘systemic thinking’ skills across three key aspects:

How they navigate technical complexity and navigate uncertainty
How they meet expectations of scale, security and speed
How they focus on the bigger picture without losing sight of details

This assessment of the end-to-end thought process and a holistic approach to problem-solving is what the interview should focus on.

What are some common topics for a System Design Interview

System design interview questions are free-form and exploratory in nature where there is no right or best answer to a specific problem statement. Here are some common questions:

How would you approach the design of a social media app or video app?

What are some ways to design a search engine or a ticketing system?

How would you design an API for a payment gateway?

What are some trade-offs and constraints you will consider while designing systems?

What is your rationale for taking a particular approach to problem solving?

Usually, interviewers base the questions depending on the organization, its goals, key competitors and a candidate’s experience level.

For senior roles, the questions tend to focus on assessing the computational thinking, decision making and reasoning ability of a candidate. For entry level job interviews, the questions are designed to test the hard skills required for building a system architecture.

The Difference between a System Design Interview and a Coding Interview

If a coding interview is like a map that takes you from point A to Z – a systems design interview is like a compass which gives you a sense of the right direction.

Here are three key difference between the two:

Coding challenges follow a linear interviewing experience i.e. candidates are given a problem and interaction with recruiters is limited. System design interviews are more lateral and conversational, requiring active participation from interviewers.

Coding interviews or challenges focus on evaluating the technical acumen of a candidate whereas systems design interviews are oriented to assess problem solving and interpersonal skills.

Coding interviews are based on a right/wrong approach with ideal answers to problem statements while a systems design interview focuses on assessing the thought process and the ability to reason from first principles.

How to Conduct an Effective System Design Interview

One common mistake recruiters make is that they approach a system design interview with the expectations and preparation of a typical coding interview.
Here is a four step framework technical recruiters can follow to ensure a seamless and productive interview experience:

Step 1: Understand the subject at hand

Develop an understanding of basics of system design and architecture
Familiarize yourself with commonly asked systems design interview questions
Read about system design case studies for popular applications
Structure the questions and problems by increasing magnitude of difficulty

Step 2: Prepare for the interview

Plan the extent of the topics and scope of discussion in advance
Clearly define the evaluation criteria and communicate expectations
Quantify constraints, inputs, boundaries and assumptions
Establish the broader context and a detailed scope of the exercise

Step 3: Stay actively involved

Ask follow-up questions to challenge a solution
Probe candidates to gauge real-time logical reasoning skills
Make it a conversation and take notes of important pointers and outcomes
Guide candidates with hints and suggestions to steer them in the right direction

Step 4: Be a collaborator

Encourage candidates to explore and consider alternative solutions
Work with the candidate to drill the problem into smaller tasks
Provide context and supporting details to help candidates stay on track
Ask follow-up questions to learn about the candidate’s experience

Technical recruiters and hiring managers should aim for providing an environment of positive reinforcement, actionable feedback and encouragement to candidates.

Evaluation Rubric for Candidates

Facilitate Successful System Design Interview Experiences with FaceCode

FaceCode, HackerEarth’s intuitive and secure platform, empowers recruiters to conduct system design interviews in a live coding environment with HD video chat.

FaceCode comes with an interactive diagram board which makes it easier for interviewers to assess the design thinking skills and conduct communication assessments using a built-in library of diagram based questions.

With FaceCode, you can combine your feedback points with AI-powered insights to generate accurate, data-driven assessment reports in a breeze. Plus, you can access interview recordings and transcripts anytime to recall and trace back the interview experience.

Learn how FaceCode can help you conduct system design interviews and boost your hiring efficiency.

AI Recruiting

How Candidates Use Technology to Cheat in Online Technical Assessments

Impact of Online Assessments in Technical Hiring In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers. The ease and...

Impact of Online Assessments in Technical Hiring

In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers.

The ease and efficiency of virtual interviews, take home programming tests and remote coding challenges is transformative. Around 82% of companies use pre-employment assessments as reliable indicators of a candidate's skills and potential.

Online skill assessment tests have been proven to streamline technical hiring and enable recruiters to significantly reduce the time and cost to identify and hire top talent.

In the realm of online assessments, remote assessments have transformed the hiring landscape, boosting the speed and efficiency of screening and evaluating talent. On the flip side, candidates have learned how to use creative methods and AI tools to cheat in tests.

As it turns out, technology that makes hiring easier for recruiters and managers - is also their Achilles' heel.

Cheating in Online Assessments is a High Stakes Problem

With the proliferation of AI in recruitment, the conversation around cheating has come to the forefront, putting recruiters and hiring managers in a bit of a flux.

According to research, nearly 30 to 50 percent of candidates cheat in online assessments for entry level jobs. Even 10% of senior candidates have been reportedly caught cheating.

The problem becomes twofold - if finding the right talent can be a competitive advantage, the consequences of hiring the wrong one can be equally damaging and counter-productive.

As per Forbes, a wrong hire can cost a company around 30% of an employee's salary - not to mention, loss of precious productive hours and morale disruption.

The question that arises is - "Can organizations continue to leverage AI-driven tools for online assessments without compromising on the integrity of their hiring process? "

This article will discuss the common methods candidates use to outsmart online assessments. We will also dive deep into actionable steps that you can take to prevent cheating while delivering a positive candidate experience.

Common Cheating Tactics and How You Can Combat Them

Using ChatGPT and other AI tools to write code
Copy-pasting code using AI-based platforms and online code generators is one of common cheat codes in candidates' books. For tackling technical assessments, candidates conveniently use readily available tools like ChatGPT and GitHub. Using these tools, candidates can easily generate solutions to solve common programming challenges such as:
- Debugging code
- Optimizing existing code
- Writing problem-specific code from scratch
Ways to prevent it
- Enable full-screen mode
- Disable copy-and-paste functionality
- Restrict tab switching outside of code editors
- Use AI to detect code that has been copied and pasted
Enlist external help to complete the assessment

Candidates often seek out someone else to take the assessment on their behalf. In many cases, they also use screen sharing and remote collaboration tools for real-time assistance.

In extreme cases, some candidates might have an off-camera individual present in the same environment for help.

Ways to prevent it
- Verify a candidate using video authentication
- Restrict test access from specific IP addresses
- Use online proctoring by taking snapshots of the candidate periodically
- Use a 360 degree environment scan to ensure no unauthorized individual is present
Using multiple devices at the same time

Candidates attempting to cheat often rely on secondary devices such as a computer, tablet, notebook or a mobile phone hidden from the line of sight of their webcam.

By using multiple devices, candidates can look up information, search for solutions or simply augment their answers.

Ways to prevent it
- Track mouse exit count to detect irregularities
- Detect when a new device or peripheral is connected
- Use network monitoring and scanning to detect any smart devices in proximity
- Conduct a virtual whiteboard interview to monitor movements and gestures
Using remote desktop software and virtual machines

Tech-savvy candidates go to great lengths to cheat. Using virtual machines, candidates can search for answers using a secondary OS while their primary OS is being monitored.

Remote desktop software is another cheating technique which lets candidates give access to a third-person, allowing them to control their device.

With remote desktops, candidates can screen share the test window and use external help.

Ways to prevent it
- Restrict access to virtual machines
- AI-based proctoring for identifying malicious keystrokes
- Use smart browsers to block candidates from using VMs

Future-proof Your Online Assessments With HackerEarth

HackerEarth's AI-powered online proctoring solution is a tested and proven way to outsmart cheating and take preventive measures at the right stage. With HackerEarth's Smart Browser, recruiters can mitigate the threat of cheating and ensure their online assessments are accurate and trustworthy.

Secure, sealed-off testing environment
AI-enabled live test monitoring
Enterprise-grade, industry leading compliance
Built-in features to track, detect and flag cheating attempts

Boost your hiring efficiency and conduct reliable online assessments confidently with HackerEarth's revolutionary Smart Browser.

The Complete Guide to Hiring a Full-Stack Developer Using HackerEarth Assessments