DEV Community: Daniel Borowski

BigO for technical interviews

Daniel Borowski — Tue, 18 May 2021 01:14:57 +0000

When preparing for upcoming technical interviews (especially for software engineering roles at FAANG companies), you might practice by solving coding challenges online and preparing by solving common interview questions.

One of our previous articles lists some common platforms where you can practice coding, like:

Big-O is an important concept you'll come across when learning about algorithms and data structures.

Big-O notation is used to classify algorithms according to how their run time or space requirements grow as the input size grows.

Coderbyte is the only platform where the runtime analysis for your solutions is generated and expressed in Big-O notation automatically in your profile. Below is a screenshot of how it'll look on your profile after solving a coding challenge.

function FindIntersection(strArr) { 
  let arr1= strArr[0].split(', ');
  let arr2 = strArr[1].split(', ');
  let intersArr= [];
  for (i = 0; i < arr1.length; i++) {
    if (arr2.includes(arr1[i])) {
      intersArr.push(arr1[i])
    }
  }
  return intersArr.toString();
}

When you submit a solution for a challenge and it passes all the test cases, your solution is then sent to our runtime-analysis server where we run a series of progressively larger test cases, and then statistically determine what runtime trajectory it matches. We currently will return one of the following common Big-O results.

We open-sourced our code for this as well (written in TypeScript) so you can learn how it works!

Hi CodeLand, we're Coderbyte and we're here to help you level up your interview skills.

Daniel Borowski — Thu, 23 Jul 2020 12:02:20 +0000

Coderbyte is the #1 coding challenge platform for interview prep. We offer a collection of code challenges and web development courses that can help you prepare for upcoming job interviews. The coding challenges range in difficulty and they can all be completed straight in our online editor!

We're so excited to be at Codeland, and hope we can help you level up your coding and interview skills. Check us out at Coderbyte.com and take the Codeland challenge today.

Here's what you can expect (psssst scroll down for a special CodeLand discount):

A CodeLand Exclusive Discount ✨

If you're excited about our approach to interview prep, then today's your lucky day! Please enjoy 30% off any subscriptions or crash courses with this special CodeLand link.

If you have any questions at all, please feel free to leave a comment down below :)

The Best Code Interview Prep Platforms in 2020

Daniel Borowski — Tue, 16 Jun 2020 04:55:17 +0000

Software developer interviews are rapidly evolving. Years ago, mastering data structures and common algorithms was enough to ace an interview and get a job. Today though, employers want candidates with real-world experience and skills.

That’s why many interviewers won’t even ask data structure or algorithm questions at all. Instead, they'll focus on proficiencies with full-stack technologies and collaboration skills.

Job seekers would be wise to practice code challenges and take mock interviews to make sure they’re prepared. There are countless books and resources, such as Cracking The Coding Interview, and popular online code challenge websites.

In addition to those resources, here are the best code interview prep platforms for developer candidates.

Coderbyte

Coderbyte, my website, is the only site to offer full-stack coding challenges, interview prep courses, and mock interviews. With 500+ challenges, articles, and videos across algorithm, front-end, and even database technologies, you can quickly assess and refine your skills for any role. We also showcase user-submitted and official solutions for all challenges.

Interview Cake

Frequently considered the best source for interview articles, tips, and content, Interview Cake is a crash course in getting a software development job.

They offer courses that are specific to leading technology companies, and provide guidance beyond solving coding problems, such as advice on how to effectively communicate with interviewers even when you don’t know the answer.

AlgoExpert

AlgoExpert is one of the original coding challenge websites. The site offers tons of video tutorials, certifications, and interview tips. Their interview prep includes a selection of 100 challenges across all types of technologies and roles.

Interviewing.io

Interviewing.io takes a very unique approach to coding interview prep. Rather than providing content and practice coding challenges, Interviewing.io has a library of actual video interviews that you can watch, and you can pay to anonymously take a mock interview with an engineering hiring manager.

You may still need to practice coding on another site, but this is a great investment to get actionable feedback.

Leetcode

Like Coderbyte and AlgoExpert, Leetcode is one of the original coding challenge websites. They offer many interview prep courses for tech companies and roles, and display the average scores for different cohorts of developers so you can easily benchmark.

HackerEarth

Famous for their coding competitions and hackathons, HackerEarth recently launched a feature for mock interviews.

They have a massive community of international developers and companies, so this is a great site if you are also looking to connect with a potential employer.

HackerRank

Known for their recruiting tools, HackerRank also offers code challenges and interview prep for developers. There's no premium version, so you can access their strong library of challenges for free. It’s a good place to start for a job seeker that isn’t sure yet if they are ready to invest in premium interview prep.

The Best Coding Challenge Websites of 2020

Daniel Borowski — Sun, 05 Jan 2020 18:17:39 +0000

Despite the lowest unemployment rate in decades, analysts expect technology hiring to continue growing steadily into the 2020s. That’s great news for recent computer science graduates and developers currently working in the field, but that doesn’t mean ambitious engineers can get complacent. While there will likely be growth opportunities in the market overall, there are still significant changes apace and urgency to keep up with the latest trends.

Today, there are more types of technical roles than ever before, and a continued proliferation of new languages, frameworks, and technologies. Technical employees that want to get ahead should routinely test and refine their skills. To that end, I’ve put together the following list of platforms where you can level up your skills for any number of roles, from data science to developer operations.

1. Coderbyte

Helpful links: Website | Challenges | Premium

Coderbyte provides 300+ coding challenges you can solve in an online editor using 10 different programming languages. You can then access official solutions, over 1.5 million user solutions, and read articles on how to efficiently solve the challenges. Coderbyte is recommended by the top coding bootcamps and companies because of its collection of interview prep challenges.

Great for…

Coderbyte is perfect for people in the beginner-to-intermediate phase of their careers. There is a library of harder challenges as well for those who like to solve coding problems for fun, but this isn’t primarily a site for competitive programmers.

Pricing / Premium content

There are a handful of free challenges on Coderbyte, and then there are hundreds of premium challenges and over 1 million user solutions that are available to members.

2. LeetCode

The 5 hardest code challenges for beginners

Daniel Borowski — Sat, 12 Oct 2019 23:03:35 +0000

On Coderbyte we offer around 100 easy code challenges that are perfect for beginners who are learning to code and need some way to practice. We looked at the stats for these challenges and found the ones where users struggled with the most to achieve a perfect score. We ended up narrowing down all the easy challenges to find the 5 hardest ones listed in the easy section — where by easy we mean challenges that should be solvable somewhere between 15–25 minutes by a beginner coder.

Hardest Beginner Challenges

Question Marks: Requires looping through a string and checking if certain conditions are met.
Vowel Square: Requires finding a 2x2 square of vowels in a larger matrix.
Scale Balancing: Requires looping through an array of weights to determine if a scale can be perfectly balanced.
Correct Path: Requires traversing through a partially finished path in an NxN matrix and finishing the path.
Closest Enemy II: Requires checking the distance between certain points in a NxM matrix.

Out of these, the challenge where users struggled most to get a perfect score and spent the longest time solving is Question Marks.

Challenge Description

Take an input string parameter and determine if exactly 3 question marks exist between every pair of numbers that add up to 10. If so, return true, otherwise return false. Some examples test cases are below:

"arrb6???4xxbl5???eee5" => true
"acc?7??sss?3rr1??????5" => true
"5??aaaaaaaaaaaaaaaaaaa?5?5" => false
"9???1???9???1???9" => true
"aa6?9" => false

Before reading further, try and think of how you would solve this challenge.

Analysis

This challenge requires several layers of logic to get right, which is why it can be difficult to come up with a solution at first. It requires looping through the string and maintaining the position of every pair of numbers that add up to 10. If you do find two numbers that add up to 10, then you will need to determine if exactly 3 specific characters exist somewhere between these two indices.

68% of users who submitted a solution in JavaScript didn’t get a perfect score.
35% of users who submitted a solution in Ruby didn’t get a perfect score.
The average number of lines for a solution is 15–29.

Sample Solutions

Below is a very concise and elegant solution written in Python by the #13th ranked user on Coderbyte, Qlogin.

def QuestionsMarks(s):
  qnum = 0
  dig = 0
  has_10 = False
  for ch in s:
    if ch.isdigit():
      if int(ch) + dig == 10:
        if qnum != 3:
          return 'false'
        has_10 = True
      dig = int(ch)
      qnum = 0
    elif ch == '?':
      qnum += 1
  return 'true' if has_10 else 'false'

There is also a clever regex solution that a user on Coderbyte implemented in Java to solve the challenge:

public static String QuestionsMarks(String str) { 

  str = str.replaceAll("[a-z]+","");
  Pattern pattern = Pattern.compile("([0-9])([?])([?])([?])([0-9])");
  Pattern pattern01 = Pattern.compile("([0-9])([?])([?])([0-9])");
  Matcher matcher01 = pattern01.matcher(str);
  Pattern pattern02 = Pattern.compile("([0-9])([?])([0-9])");
  Matcher matcher02 = pattern02.matcher(str);
  Matcher matcher = pattern.matcher(str);

  if (matcher01.find() || matcher02.find()) {
    return "false";
  } else if (matcher.find()) {
    return "true";
  }

  return "false";

}

Try out the challenges for yourself on Coderbyte and comment below on what you think about the sample solutions!

This article originally appeared on Medium.

Improving your Algorithms & Data Structure skills

Daniel Borowski — Wed, 09 Oct 2019 14:22:37 +0000

Fundamentals

The first thing you’ll need if you want to get better at algorithms and data structures is a solid base. This base can be learned one of several ways, either through a computer science program at university, some coding bootcamps focus a bit on the topics below, or you can learn on your own from books, videos, or online lectures. So you’ll need a basic understanding of the following topics to get started:

Data Structures

Learn about arrays, linked lists, binary trees, hash tables, graphs, stacks, queues, heaps, and other fundamental data structures.

Computer Architecture

Learn how data is represented in a computer, the basics of digital logic design, boolean algebra, computer arithmetic, floating-point representation, cache design. Try and learn a little about C and Assembly programming.

Moving Forward Past the Fundamentals

Once you feel like you have a good understanding of most of the concepts listed above, it’s time to start diving into the algorithms part. Here is a list of resources and things I did to get better at writing and understanding important algorithms.

Big-O & Runtime

Learn what Big-O is and how to analyze the running times of algorithms. This is a classic book on the topic (here is the chapter on the growth of functions).
Here is a good list of online courses that teach algorithms.

Implement Some Algorithms Yourself

Start off by implementing several important algorithms yourself and learning about their running times. Some examples are:

Binary search
Euclid’s algorithm
Depth and breadth first search
Dijkstra’s shortest path
Binary tree traversals
Insertion sort, Mergesort, Quicksort
Min & max heaps
More examples and lists.

Algorithm Books

Read the Algorithm Design Manual. It’s a great book and it’s my favorite.
Introduction to Algorithms is a classic book that covers a lot of material.
Elements of Programming Interviews contains a lot of challenges and code solutions that will help you prepare for interviews.

Challenges

Practice coding simple and then more advanced algorithms on sites like Coderbyte which provide explanations and solutions so you can learn from other coders as well.
Go through the challenges on this interactive python algorithms website.
The 10 most popular coding challenge websites for 2018.
The 5 hardest code challenges for beginners.

Algorithms Explanations & Interview Questions

Read as many algorithm explanations and code examples as you can on GeeksforGeeks. Here is an example of a good post on graph algorithms.
Look at some interview questions posted on CareerCup and try and understand how other users solved the questions. Like this example.
Aside from coding challenge sites, try and solve common coding interview questions you find online such as the ones on this list.

Dynamic Programming

This a very important concept you will need to understand if you want to get better at algorithms, which is the reason I separated this topic from the rest. The description from Wikipedia for it 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. The next time the same subproblem occurs, instead of recomputing its solution, one simply looks up the previously computed solution, thereby saving computation time.

I have seen dynamic programming show up in several coding interviews I’ve had. I’ve also seen problems that require a dynamic programming solution on challenge sites like LeetCode, Google Code Jam, and several challenges on Google Foo Bar required a DP solution.

I’d recommend to try and solve as many problems on this list as you can. There is also a good tutorial on TopCoder titled: Dynamic Programming — From Novice to Advanced. A lot of DP problems have the same structure and patterns so if you solve 3 DP problems everyday for 2 weeks or so, after a while you’ll be able to spot and solve a DP problem no problem.

Advanced Resources in Algorithms (optional)

Advanced Data Structures Lectures by Erik Demaine
Algorithmic Lower Bounds: Fun with Hardness Proofs by Erik Demaine
Competitive Programmer’s Handbook
The Hitchhiker’s Guide to the Programming Contests
AlgoWiki: A wiki dedicated to competitive programming
Open Data Structures Book: implementation and analysis of data structures for sequences, queues, priority queues, unordered dictionaries, ordered dictionaries, and graphs

I hope you enjoyed this list of resources. Feel free to practice coding on Coderbyte, and comment below with any other resources you think are helpful.

This article originally appeared on Medium.

A tricky JavaScript interview question asked by Google

Daniel Borowski — Mon, 07 Oct 2019 23:19:35 +0000

The following will be a short explanation, along with some solutions, of a popular JavaScript question that tends to get asked in developer interviews. The question usually looks something like the following:

// interviewer: what will the following code output?
const arr = [10, 12, 15, 21];
for (var i = 0; i < arr.length; i++) {
  setTimeout(function() {
    console.log('Index: ' + i + ', element: ' + arr[i]);
  }, 3000);
}

This question deals with the topics: closures, setTimeout, and scoping.

The correct answer to this is question is:

Index: 4, element: undefined
Index: 4, element: undefined
Index: 4, element: undefined
Index: 4, element: undefined

If that’s not what you expected, then hopefully the rest of this article will help explain why this is the case in JavaScript.

Why is this question so popular?

A user on reddit mentioned that they were asked this question in an Amazon developer interview. I’ve also been asked this type of closure + loop question in interviews myself — even in a Google interview.

This question tests your knowledge of some important JavaScript concepts, and because of how the JavaScript language works this is actually something that can come up quite often when you’re working — namely, needing to use setTimeout or some sort of async function within a loop.

A solid understanding of functional/block scope, anonymous functions, closures, and IIFE’s will definitely make you a better JavaScript developer and help you out in future interviews.

Solutions

I've written about this particular type of challenge on Coderbyte and on freeCodeCamp as well.

The reason for this is because the setTimeout function creates a function (the closure) that has access to its outer scope, which is the loop that contains the index i. After 3 seconds go by, the function is executed and it prints out the value of i, which at the end of the loop is at 4 because it cycles through 0, 1, 2, 3, 4 and the loop finally stops at 4. arr[4] does not exist, which is why you get undefined.

There are two popular solutions to the question. One involves passing the needed parameters into the inner function, and the other solution makes use of ES6.

const arr = [10, 12, 15, 21];
for (var i = 0; i < arr.length; i++) {
  // pass in the variable i so that each function 
  // has access to the correct index
  setTimeout(function(i_local) {
    return function() {
      console.log('The index of this number is: ' + i_local);
    }
  }(i), 3000);
}

const arr = [10, 12, 15, 21];
for (let i = 0; i < arr.length; i++) {
  // using the ES6 let syntax, it creates a new binding
  // every single time the function is called
  // read more here: http://exploringjs.com/es6/ch_variables.html#sec_let-const-loop-heads
  setTimeout(function() {
    console.log('The index of this number is: ' + i);
  }, 3000);
}

A user on the reddit post provided a similar answer to this question as well. There’s also a good explanation of closures by a user on Stack Overflow.

This often confuse people who are new to JavaScript or functional programming. It is a result of misunderstanding what closures are. A closure does not merely pass the value of a variable or even a reference to the variable. A closure captures the variable itself!

Thanks for reading! Check out Coderbyte for some coding practice :)

This article originally appeared on Medium.