I would argue that it's a pretty good measure of programming and CS problem solving skill with weak alternatives.
Now, I do get that there's a lot of people who don't like spending time at home for interview tasks but when you think about AND it's not skewed to extreme (say, big task 8 working hours worth) then, in terms of time wasted, it's not such a big difference. Interviewer can then see the code quality, can talk about it with candidate, clarify some missing pieces or pitfalls found, etc.
IMHO most important is not if the candidate knows how to solve some hard or even medium problem when I speak to them and they are stressed enough already. What is important is if they're willing to learn, if they know how to search for stuff they may not know and if they can produce performant enough, but excellent to read, code.
Interviewing in eng is broken, but afaict its a “worst solution save all others” kind of scenario.
But let us not begin to deem these intrinsically important.
Some of the most creative and productive coworkers I’ve had struggled with leetcode style interviews. They’re a bad tool for anyone who isnt a new grad, and even then.
The point is not (or shouldn't be) to recite a textbook. The point is you can navigate your way around the textbooks. I've got both The Art of Computer Programming and The Art of Electronics on my shelf. I could find the sections to help sorting a list in seconds. As for the latter, I have no idea why the majority of that book even exists. I can't call myself an electrical engineer, even though all the theory I need is within arm's reach.
I assume you're arguing against the "recite the textbook" approach. I would agree that this is not the way to do things. But equally, "throw the textbooks out" is not the right way either. We need to evaluate a high-level grasp of the literature/theory but don't punish for forgetting minutiae. I might ask a candidate to talk about choice of sorting algorithms. There is, of course, no perfect answer, but what I'll be expecting is general evaluation of algorithms: time/memory tradeoffs, probing for more domain knowledge (e.g. does the data often come in sorted or random), platform constraints etc. I won't even expect a name drop of an actual sorting algorithm as that's not really the point. What they're telling me is they know why Knuth has a whole chapter on sorting. That's the important thing.
I'd much rather hire and work with someone who has the skill to easily assess a situation and use referencing to rebuild knowledge than someone who memorised how to implement tree balancing, so why do we test for the latter rather than the former?
Stop supporting baseless metrics for assessment just because some old person used them before you showed up. We can and should do better.
It could be that by changing interview strategy to look more similar to other professions that profit can be increased even farther, but nobody is risking it.
And I can ask that given the recent issues with data privacy and data abuse by the tech giants, would we be in this place if the interview processes had selected for more holistic engineers, technically able but that refuse to play the game just for the sake of playing the game, that are opinionated and don't conform to something just for the sake of money?
I know that I might be creating a false dichotomy but I would like to think about what kind of pressure this selection process creates, what biases arises from it? How can we make it better?
Because your argument is the most conservative and pro-establishment one: it works so don't touch it and just emulate.
Not everyone is playing the absurdly doofy “game,” just most.
Local maximum that laziness has us trapped in. Nothing to do with merit.
Yes it is.
> Theory can be referenced
How do you know that the person is even able to comprehend theory?
> Interviewing in eng is broken, but afaict its a “worst solution save all others” kind of scenario.
That's your opinion.
> Some of the most creative and productive coworkers I’ve had struggled with leetcode style interviews.
Good for you. But "slumpt_'s most creative and productive coworkers" is not a good metric for hiring.
> They’re a bad tool for anyone who isnt a new grad, and even then.
Again, that's your opinion. I'm not a pro in those interviews, but studying DS and algos opened up and pushed my mind to its limits like nothing else. Your whole thinking process changes when you start working on this, you start thinking about constraints, performance implications, pro and cons of different approaches. It is called Computer SCIENCE for a reason.
The point is neither is demonstrated to bear any relationship to jack shit
Interviewing is and has been broken, even with the changes we’ve made over the years.
If you’re holding onto leetcode challenges that make you think hard as representative of engineering prowess we’re never going to have a reasonable conversation.
Define this first.
I was into competitive math as a teenager and was somewhat successful, but I actually kind of suck at math.
Similarly, I'm a professional developer but I'm really bad at competitive programming: what usually happens is that I know how to solve the problems but the time limit is too low (for me, at least).
I'd say success in competitions is a good indicator of dedication and perseverance, but not sufficient to spot someone who's good at the job.
Sure if you're applying for a job that really demands algorithmic design skills it should be a great asset but in general the most valuable skills any programmer has is producing simple and robust code that works and others can continue building on. I don't deny that knowing algorithmic design skills well helps a lot but it does seem to feed the egos of the programmers to produce overly complicated solutions.
I'd answer this type of algorithm question in truth by identifying the relevant library wherever possible, not by coding it myself, and I'd strongly expect anyone I was working with to do the same.