Cracking the Coding Interview: 189 Programming Questions and Solutions (Cracking the Interview & Career)

worth the hype

I’ve been meaning to review this book for a while. Last year I got laid off from my startup and found myself feeling anxious as I haven’t had to look for a job for several years. I bought this book along with two others, but this was the only one I really spent time on. The first third of this book provides specific information about companies along with example problems. The last two thirds are problem solutions with explanations. I found everything valuable. I didn’t write out complete solutions for most of her example problems. If I thought it was obvious I skipped it, but whatever you do don’t skip reading the solution. It’s here where you can read about ways of solving the problem that didn’t occur to you. For example, if you want to know if two binary trees are identical you can verify this by comparing their preorder and inorder traversals. The only gaps were discrete math and heaps. Heaps appeared frequently in sample questions on Glassdoor. I pulled an old data structures book out to re-read about heaps, but I was never explicitly asked about them during my job search though I did mention them a couple times as possible ways to maintain a priority queue.Information about the companies was very relevant as I live in the Bay Area. I wish I had heeded her admonition about discrete math for Google because I was unprepared for these questions. I would have read the math if it was in the book, but since I haven’t used that math ever in a job I skipped it. During the interview I was able to solve the math problems except I needed basic definitions and one or two hints. For Amazon it was good to know there’s a “bar raiser” because it was obvious when I met the interviewer who wrote out a really hard problem right off the bat and wanted a linear time algorithm. I was speechless for five minutes, but managed to reduce the problem enough where the solution suddenly came to me. I think I would have been unnerved by the question if I didn’t know about this type of interviewer that she writes about. I wish she also covered Twitter and LinkedIn.The book doesn’t talk enough about applying for jobs. I do wish she wrote about job offer contingencies as my first job offer was from a startup who told me it expires in 24 hours. This in turn caused other recruiters to panic. While in the end I got a good job, all in all I hope I’m not forced to do this again anytime soon. I’m just glad I had this book at my side. It was indispensable.

While this book is meant for interview practice, I would recommend you still read it just for fun if you're into algorithms.I've always believed that there's no "crack" to coding interviews; it's just a matter of whether you can code or not (well, at least at those sane companies not filling up school buses with golf balls). And that requires practice. Lots of practice. Which is why I spent all my free time working out problems on Hackerrank. For me, this went well . . . for a while.But there comes a point at which you get stuck. I remember working on some hackerrank problems in the medium to hard difficulty which I would not be able to proceed for weeks and weeks. No amount of googling for information, discussion boards or stack overflow threads paint a complete picture to help you when you're stuck.After countless such occasions and failing a few interviews, I gave in and bought this book. After all it was $20 - the cost of an uber to work.Now, I wish I had bought this sooner!Within reading the first two chapters I've already learnt so much about how to think about coding problems. There's also a nice collections of custom data structures at the end of the book. I've swiped some data structures straight out of this book and use them in my day-to-day life too.Gayle has done a tremendous job of using words to explain how that weird gooey gel inside your head moves like when problem-solving. She deconstructs every approach to tackle a problem into atomic pieces. She goes into great depth about alternative designs, tradeoffs and runtime complexity. She talks about visualizing recursive calls as trees, thinking about BUD*, amortized analysis of ArrayList and much more. The great thing is that Gayle goes into copious amounts of details for each solution - she talks about how to start from a brute force solutions and optimize each component one-by-one and talks about tradeoffs in approaches.Overall, I think this a very helpful book. I would recommend you begin reading this book immediately after your first course on Algorithms. It will certainly help drill down the concepts and help strengthen your fundamentals.*BUD is a special term the author uses to describe strategies to optimize solutions