Back in 2015, I went through some coding interviews and got offers from several large tech companies. So at that point, I decided to share what I'd learned in this article.
And I've just updated it for 2022 so it'll be super useful and relevant if you're job hunting now.Despite scoring decent grades in both my CS101 Algorithm class and my Data Structures class in university, I shudder at the thought of going through a coding interview that focuses on algorithms.
Hence I spent the last three months figuring out how to improve my coding interview skills and eventually received offers from big tech companies like Google, Facebook, Airbnb, Lyft, Dropbox and more.
In this post, I’ll be sharing the insights and tips I gained along the way. Experienced candidates can also expect System Design questions, but that is out of the scope of this post.
Many of the algorithmic concepts tested in coding interviews are not what I usually use at work, where I am a Front End Engineer (web). Naturally, I have forgotten quite a bit about these algorithms and data structures, which I learned mostly during my freshmen and sophomore years of college.
It’s stressful to have to produce (working) code in an interview, while someone scrutinizes every keystroke that you make. What’s worse is that as an interviewee, you’re encouraged to communicate your thought process out loud to the interviewer.
I used to think that being able to think, code, and communicate simultaneously was an impossible feat, until I realized that most people are just not good at coding interviews when they first start out. Interviewing is a skill that you can get better at by studying, preparing, and practicing for it.
My recent job search has led me on a journey to improve my coding interview skills. Front End Engineers like to rant about how the current hiring process is broken because technical interviews can include skills not related to front-end development. For example, writing a maze solving algorithm and merging two sorted lists of numbers. As a Front End Engineer myself, I can empathize with them.
Front end is a specialized domain where engineers have to care about many issues related to browser compatibilities, the Document Object Model, JavaScript performance, CSS layouts, and so on. It is uncommon for front-end engineers to implement some of the complex algorithms tested in interviews.
At companies like Facebook and Google, the people are software engineers first, domain experts second.
Unfortunately, rules are set by the companies, not the candidates. There is a high emphasis on general computer science concepts like algorithms, design patterns, data structures; core skills that a good software engineer should possess. If you want the job, you have to play by the rules set by the game masters — improve your coding interview skills!
This post is structured into the following two sections. Feel free to skip ahead to the section that interests you.
- The breakdown of coding interviews, and how to prepare for them.
- Helpful tips and hints for each algorithm topic (arrays, trees, dynamic programming, etc.), along with recommended LeetCode practice questions to review core concepts and to improve on those topics.
The content for this post can be found here. I'll make updates there when necessary.
If you are interested in Front End content, check out my front end interview handbook here.
Picking a programming language
Before anything else, you need to pick a programming language for your algorithmic coding interview.
Most companies will allow you to code in the language of your choice. The only exception I know is Google. They allow their candidates to pick from only Java, C++, Python, Go or JavaScript.
For the most part, I recommend using a language that you are extremely familiar with, rather than one that is new to you but that the company uses widely.
There are some languages that are more suitable than others for coding interviews. Then there are some that you absolutely want to avoid.
From my experience as an interviewer, most candidates pick Python or Java. Other languages commonly selected include JavaScript, Ruby, and C++. I would absolutely avoid lower-level languages like C or Go, simply because they lack standard library functions and data structures.
Personally, Python is my de facto choice for coding algorithms during interviews. It is succinct and has a huge library of functions and data structures.
One of the top reasons I recommend Python is that it uses consistent APIs that operate on different data structures, such as len(), for ... in ... and slicing notation on sequences (strings, lists, and tuples). Getting the last element in a sequence is arr[-1] , and reversing it is simply arr[::-1]. You can achieve a lot with minimal syntax in Python.
Java is a decent choice too. But because you will have to constantly declare types in your code, it means entering extra keystrokes. This will slow down the speed at which you code and type. This issue will be more apparent when you have to write on a whiteboard during on-site interviews.
The reasons for choosing or not choosing C++ are similar to Java. Ultimately, Python, Java, and C++ are decent choices. If you have been using Java for a while, and do not have time to become familiar with another language, I recommend sticking to Java instead of picking up Python from scratch. This helps you to avoid having to use one language for work and another one for interviews. Most of the time, the bottleneck is in the thinking and not the writing.
One exception to the convention of allowing the candidate to “pick any programming language they want” is when the interview is for a domain-specific position, such as front-end, iOS, or Android engineer roles. You need to be familiar with coding algorithms in JavaScript, Objective-C, Swift, and Java, respectively.
If you need to use a data structure that the language does not support, such as a queue or heap in JavaScript, ask the interviewer if you can assume that you have a data structure that implements certain methods with specified time complexities. If the implementation of that data structure is not crucial to solving the problem, the interviewer will usually allow it.
In reality, being aware of existing data structures and selecting the appropriate ones to tackle the problem at hand is more important than knowing the intricate implementation details.
Review your CS101
If you have been out of college for some time, it is highly advisable to review the CS fundamentals. I prefer to review it as I practice. I scan through my notes from college and revise the various algorithms as I work on the algorithm problems from LeetCode and Cracking the Coding Interview.
If you are interested in how data structures are implemented, check out Lago, a GitHub repository containing Data Structures and Algorithms examples in JavaScript.
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