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Inside Tips on how to ace coding interviews in top companies

Inside Tips on how to ace coding interviews in top companies

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Vaibhav Sharma
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September 16, 2020
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6 min read
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“Software is a great combination between artistry and engineering.”
– Bill Gates

In college, I wanted to learn to build things that would have a significant and positive impact on mankind. I looked around and saw that there were people and organizations out there that were doing this on a daily basis. They were pushing the human race forward with their numerous contributions to society. But unfortunately for me, I was not able to find anyone/anything that could show me the path to these organizations or offer me the necessary guidance toward cracking their coding interviews. I discovered how to ace coding interviews the hard way, by getting knocked from one resource to another, finally securing offers from HackerEarth, Microsoft, Airbus and GeeksforGeeks in my final year. This was why I wanted to share my learning with whoever’s now looking for that guide. They can invest their time and energy in the right direction from the very beginning.

A lot of people who are job hunting want to know just how to land a great job at a swanky company. They want to know what are all the types of questions asked in their interviews and the topics that they should prepare for. If you are one of those people, you are in the right place. We hope that we will be able to help you prepare and ace your coding interviews!

So, you want to hold a cool job as a Software Engineer in FAANG (Facebook, Amazon, Apple, Netflix and Google), eh? Not that it’s wholly impossible but let’s backtrack a bit.

You first need to know everything that your interviewer wants to know about you. To be able to crack their coding interview, you need to broadly exhibit these 3 important skills:

  1. Problem Solving Ability (Data Structures and Algorithms)
    These make up the bulk of the coding interviews. The intent here is to assess your problem-solving skills and the questions are typically around concepts of Algorithms and Data Structures. A rookie mistake to make during these interviews is to start coding too soon. In the first 10 minutes of the interview, try seeking more clarity on the question. For example, try asking details of the expected input with questions like “Will there be any negative inputs?” and explaining the solution approach. It also helps to think out loud, that way the interviewer gets to understand your thought process and, if you are lucky, gives you hints early on if he/she sees you going in the wrong direction. Only begin writing code once you and your interviewer agree that this is the best possible approach for the solution.
  1. Domain knowledge (includes core subjects of CS)
    It is a no brainer that if you are interviewing for the role of Frontend Engineer – then you will, without a doubt, be questioned on basic technologies like HTML, JavaScript, React, etc. These are the domain skills specific to the job role that you are applying for. So, be sure to read the job description thoroughly and prepare yourself for these questions.There are a few skills that are common across the majority of software job roles and are, in fact, the core concepts of Computer Science. These include, but aren’t limited to:
    Object-Oriented Programming (OOP), Operating Systems, Databases, Computer Networks, Caching and Web Technologies.
  1. Communication skills
    This might seem like a cliche but trust me it is not. A large part of what developers do daily involves effective communication and collaboration. Communication is not just knowing what to say – it is about the how, the when, and the where, as well. You need to know how to put your point across with just the right level of detail; you need to know when to ask for help and not be the cause for decreased levels of productivity; and finally – you should know where, i.e, in which channels you need to communicate in, so your information doesn’t get lost and reaches the right people. In a nutshell, you need to communicate in a way your job gets done in the most simple and quick manner.There is also a 4th skill to know and master – systems design –but that’s something only for more experienced job-seekers applying for senior software engineering positions.

Approach based on time left for the interview.

Before giving you the scoop on the hot topics in interviews and their associated questions, let us discuss our battle strategy to tackle it. It’s usually beneficial to prepare for interviews according to the time you have left before it. Makes sense, right? Well, let’s jump right in!

1-3 months to interview:

Oh boy, less than 3 months to showdown. Since we can never actually know which data structure or algorithm might be asked, here it is a good idea to get a working knowledge of as many topics as you possibly can. What this means is, we are going for a ‘jack of all trades’ approach rather than ‘master of one’.

if ( !agreeWithThis )

{

For the people who disagree with this point of view, let me try and convince you – suppose you spend the bulk of your prep time and ace one of the most asked topics: arrays. Now imagine you show up to the interview and the interviewer asks you a question from graphs – bonkers, right? However, if you have the basics down, maybe you can somehow work on a solution, which will be much better than thinking about X-Y axes on hearing graphs”.

}

Convinced? Great! You should go for a Breadth-First approach on topics and just prepare enough questions from each topic to get a hang of the concept. Do not spend a lot of time on any one specific topic. What this means can differ from person to person. One might take 8-10 questions to get the topic straight, while another might do it in 4-5. What’s important is that you do not cross the 10-12 question threshold, or else you’ll be eating into the time of another topic.

Resources to definitely follow: Cracking the Coding Interview by Gayle McDowell

3-6 months to interview

This can be one of the most ideal timelines. You have enough time to get a good grasp on the topics while you’re still not so far along from the interview that you’re not motivated enough. You should follow the breadth-first approach described above and spend more time on topics to get a good grasp on them.

Simultaneously, try building small projects alongside. My recommendation is that you start with your web portfolio. Besides the benefits of having a personal portfolio, it will also give you an idea of how to build and publish a website on your own. You can add other projects in here as well.

A good way to get hands-on experience with cool projects is to participate in Hackathons. They are short tech events in which teams of developers get together to build a solution to a proposed problem. They are a great way of learning how to collaborate, working well in a team, and to upskill yourself. You can find all Hackathons going on at HackerEarth here.

Would you like to get updates once a month on our latest articles? We won’t spam, we promise. Subscribe now to The HackerEarth Blog!

6+ months to interview

Boy, oh, boy, are you gonna nail this interview or what? Since you have a lot of time to prepare, we suggest that after getting comfortable by doing the above things, you can start contributing to open source projects on GitHub. You can Google “good first issue” to start with. Repository maintainers put this tag on issues to make it easier for freshers to start contributing to open source. Also, give another go at the questions. You will refresh your memory and might even come up with a better or more concise way of solving them.

The Problems:

Without further ado, let me present to you the most commonly asked topics in competitive interviews. Each topic will have one tutorial article and a few questions associated with it. You can directly attempt the questions if you are comfortable with the topic. The questions have been chosen to help you solidify your understanding of the topic and also serve as a test. Ideally try and maintain a healthy ratio of 3-6-1 of easy, medium and hard problems.

  1. Arrays:
  2. Binary Search:
  3. Sorting:
  4. Stacks:
  5. Queues:
  6. Hash Maps and Tables
  7. Linked List
  8. Trees
  9. Dynamic Programming (DP)
  10. Strings
  11. Graphs

Some tips on interviewing w/ special note on remote interviewing:

  1. Go to the company’s careers page and read up on their job description. They do tell you everything that you need to know about that role.
  2. Create mock interviews by yourself by pairing up with friends who are also interviewing for a similar job. Try to simulate real interviews as much as possible by interviewing over a video call and perhaps use a shared doc to write code. Give each other pointers on what went well and what did not.  
  3. When applying, make sure that you don’t put all your eggs in one basket. Apply to a whole range of companies and job roles to significantly increase your chances of receiving an offer.
  4. Most companies have a distinct pattern in which they take interviews. For example, Amazon conducts 5-6 rounds of interviews and they like to emphasize a lot on their leadership principles (LPs). In this case, it would be prudent to be well prepared and research beforehand about the same, so you know exactly what to expect.

Last but not the least, go communicate with people and read about their past experiences of interviewing at the companies that you are now applying for. And remember to give back and share your experiences too, so that that might help someone in need!

So, all the very best, and may the odds be ever in your favor!

Developers Interview tips

I am a SWE in the community team at HackerEarth. I enjoy building things with code, reading books and playing the occasional sport.

Vaibhav Sharma

Product marketing manager

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September 16, 2020
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6 min read
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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.

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.

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


  1. 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
  2. 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
  3. 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
  4. 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.
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