"...if you're trying to get better at technical interviews, the best way to do that is to actually do it."<p>No dammit, I don't want to get better at technical interviews - I want to live in a world where we don't need them. Why not fix the root problem instead of amplifying it?
This is valuable. Thank you for creating and posting it.<p>First, it's an excellent reference for people who don't really understand technical "interviews" and their exam-like nature. Most interviews in other fields do probe knowledge, but interviews in our fields really are exams.<p>Another factor is that there's very little knowledge of information out there. We take these exams under conditions of secrecy, with very little feedback. For example, there are scores for my performance on interview exams in a database somewhere at google, but I'm not allowed to know how they were judged, who scored them, or what the scores are. I actually don't know what would be considered a good or bad performance. This site helps me get a better sense of how these are conducted and evaluated.<p>From a business point of view, it's also clever. People really do want to get feedback, the kind they can't get from Google or other interviewers, in part because of liability issues. So by providing an area to practice, the placement site can identify people who are most likely to get through the technical interview - which means they are most likely to place candidates. Not bad.<p>That said... I'm still not surprised that people who have the skill and focus to become software developers take a look at how tech interviews work and decide that they would much rather work in a different field.
The complexity of the forwarded message problem is wrong. Any algorithm solving this can be used to answer whether a graph of order n is Hamiltonian by simply asking if the longest forwarding path is of length n-1. Thus, either the complexity is nonpolynomial or the interviewee has just won the million dollar prize for solving an NP-complete problem in polynomial time.
These recordings are really useful. Does anyone know how representative these are from actual interviews? For example, for the interview question on finding pairs in array that sum to k, the case where duplicate numbers in input array sum up to k is missed, and the interviewer didn't bring it up. Also, the space complexity of in-place quick sort is log(n), since the indices need to be kept in each call to sort subpartitions.
The audio quality of these interviews made me grimace. Audio quality aside, this looks like it would be a great resource for anyone trying to go through a "FAANG-style" multi-round interview process.