Is it worth reading Cracking the coding Interview?

If you’re ready to start interviewing with FAANG companies, Cracking the Coding Interview is worth your time and investment. It covers everything from the interview process to special situations, pre-interview preparation to behavior questions, Big O to technical questions, to 189 real-world programming questions.

Is TopCoder better than LeetCode?

If your coding skills are already sharp and you’re looking for more of a challenge, go for TopCoder. The main pros of LeetCode is their UI. it gives you more friendly look than other legacy programming platforms. Even though LeetCode has competitive problematic questions it mainly based on Interview Questions.

What is cracking the coding interview by crackingcrackingcoding?

Cracking the Coding Interview is basically two books in one. The first 90 or so pages goes over what to expect during the interview. And how to prepare for it. Then, there are hundreds upon hundreds of pages of coding problems, hints, and solutions. You might be thinking, “I’m still not convinced.

Is cracking the coding interview worth it in 2021?

Yes, Cracking the Coding Interview is worth it in 2021. The book features nearly 200 programming questions and solutions asked by Google, Amazon, Facebook, Microsoft and more. In addition, the author gives a detailed rundown of what to expect for each company’s recruiting process, how to prepare, and what is unique about their interview.

What is the best book for prepping for coding interviews?

With Cracking the Coding Interview, I think it is the best book for prepping for interviews and I highly highly recommend that you get a copy if you haven’t already. And it doesn’t even matter you don’t even need the most recent edition any edition will do. It’s just a really good starting point.

What is the Big O in cracking the coding interview?

McDowell dedicates a huge section of Cracking the Coding Interview to the Big O: 1 Analogies 2 Time and space complexity 3 Dropping constants, non-dominant terms 4 Multi-part algorithms 5 Amortized time 6 Log N runtimes 7 Recursive runtimes