>The point of these problems is to test your cleverness.
In my experience, interviewers love going to the Leetcode "Top Interview 150" list and using problems in the "Array String" category. I'm not a fan of these problems for the kind of jobs I've interviewed for (backend Python mostly), as they are almost always a "give me a O(n) runtime O(1) memory algorithm over this array" type challenge that really doesn't resemble my day to day work at all. I do not regularly do in-place array algorithms in Python because those problems are almost always handled by other languages (C, Rust, etc.) where performance is critical.
I wish interviewers would go to the "Hashmap" section for interviews in Python, JavaScript, etc., type of languages. They are much less about cleverness and more about whether you can demonstrate using the appropriate tools in your language to solve problems that actually do resemble ones I encounter regularly.
There's also the problem of difficulty tuning on some of these. Problem 169 (Majority Element) being rated "Easy" for getting a O(n) runtime O(1) memory solution is hilarious to me. The algorithm first described in 1981 that does it (Boyer–Moore majority vote algorithm) has a Wikipedia page. It's not a difficult to implement or understand algorithm, but its correctness is not obvious until you think about it a bit, at which point you're at sufficient "cleverness" to get a Wikipedia page about an algorithm named after you. Seems excessive for an "Easy" problem.
Majority Element is rated easy because it can be trivially solved with a hashmap in O(N) space and that's enough to pass the question on Leetcode. The O(1) space answer is probably more like a medium.
Honestly in day to day programming I find data types & associated APIs are so so much more important than algorithms.
I would rather work with a flexible data type with suboptimal performance than a brittle data type that maybe squeezes out some extra performance.
Your example of in-place array mutation feels like a good example of such a thing. I feel like there should be a category of interviewing questions for "code-safety" not just performance.
Interviews should not be about cleverness. They should test that you can code. I almost never write an algorithm because all the important algorithms are in my standard library already. Sure back in school I did implement a red-black tree - I don't remember if it worked, but I implemented it: I can do that again if you need me to, but it will take me several days to get all the details right (most of it looking up how it works again). I use red-black trees all the time, but they are in the language.
You need to make sure a candidate can program so asking programing question make sense. However the candidate should not be judged on if they finish or get an optimal or even correct answer. You need to know if they write good code that you can understand, and are on a path that if given a reasonable amount of time on a realistic story would finish it and get it correct. If someone has seen the problem before they may get the correct answer, but if they have not seen it they won't know and shouldn't expected to get the right answer in an hour.