Usually they give you a problem where you have to deal with large amount of data and dynamic programming problems.
Big O notation is really important. They will ask you what's the time complexity of your solution and how you can improve it. You have to be able to identify possible bottlenecks in your solution. E.g. if your solution is O(n2) they will ask you if you can solve it in O(nlogn) or O(n) and why.
Thank you very much for the reply, Brian. I'll keep improving this part of computer science.
Oh if only the job consisted of sitting around in academic conversations about Big O notation.
I think once you start measuring the time and space complexity of your algorithms you will be more aware about performance and prepare your code to handle big amounts of data. And that's important for companies, to verify that you, as a candidate, know all those concepts.
Yes, I agree with that assumption. Give the candidate a problem to solve and assess whether or not they in practice they used the most performant algorithm. We don't need to have a discussion about all the different algorithm that could have been applied to the problem. I find too much time is wasted focusing on this singular topic in interviews.
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