I've never seen this problem before and arrived at the optimal solution to the first section, sans code, in about 10 seconds. Despite that, there's almost no way I would pass a technical interview at Google.
The only reason I can think that the optimal solution was immediately obvious to me is perhaps because in a previous life I did a lot of work building convoluted application specific indexing schemes for data in a distributed KV store that had basically zero useful built-in secondary indexing schemes where piles of parallel GETs were about as "free" as just doing one, but chaining strings of requests back & forth to the client iteratively made for sad times. This meant that it was essential to be clever about what could be coded into key names and precomputed from application/use-case context to know what keys to fetch "all at once" to gather as much relevant data as possible with as few serially dependent requests as possible. One such use case depended on a modified C-trie as part of the solution, so I got very familiar with what kinds of problems they're for and what their limitations are.
Given that, I can't tell what that says about the question, about me, or about Google. What I can say for sure is that because I can't tell the above, the technical interview at my company is signing an NDA and sitting down for a couple hours and just actively pairing on real work & real problems with real teammates.
With the nature of software development work being what it is, I really don't understand why we as an industry run interviews like they're game shows or try to manufacture workplace simulators with terrible model conformance.
> Despite that, there's almost no way I would pass a technical interview at Google.
You could get lucky and have each question have a similar relationship to past knowledge. It's happened to me before, I blew through an Amazon interview once that way, but got knocked for technical leadership. So maybe you mean something like that, but that too is random. I had passed the leadership but failed the algorithms at Amazon a few years prior.
> I really don't understand why we as an industry run interviews like they're game shows or try to manufacture workplace simulators with terrible model conformance.
I believe these tests are more about compliance and baseline cognitive ability than anything else, which is good for the nature of the FAANG role. They are testing that you are willing to study what they tell you and that you are able to retain material of that level of difficultly and demonstrate that in an adversarial situation.
I also came up with the optimal solution in 3 seconds, because for my side “hustle” I work on scrabble apps all night and compressed tries are an integral part of move generation.
The only reason I can think that the optimal solution was immediately obvious to me is perhaps because in a previous life I did a lot of work building convoluted application specific indexing schemes for data in a distributed KV store that had basically zero useful built-in secondary indexing schemes where piles of parallel GETs were about as "free" as just doing one, but chaining strings of requests back & forth to the client iteratively made for sad times. This meant that it was essential to be clever about what could be coded into key names and precomputed from application/use-case context to know what keys to fetch "all at once" to gather as much relevant data as possible with as few serially dependent requests as possible. One such use case depended on a modified C-trie as part of the solution, so I got very familiar with what kinds of problems they're for and what their limitations are.
Given that, I can't tell what that says about the question, about me, or about Google. What I can say for sure is that because I can't tell the above, the technical interview at my company is signing an NDA and sitting down for a couple hours and just actively pairing on real work & real problems with real teammates.
With the nature of software development work being what it is, I really don't understand why we as an industry run interviews like they're game shows or try to manufacture workplace simulators with terrible model conformance.