Makes a lot of sense, you could solve all these questions without knowing specific algorithms as long as you are good at problem solving - which is, I assume, the intent of the process.
Obviously it doesn't always work like that.
You could solve all these questions as long as you are good at problem solving, *given enough time*.
However, with tight time constraints and perfomance pressure, the only way you could solve all these questions is memorizing and practicing all these algorithms.
Apparently the correct answer is to use "Robert W. Floyd's tortoise and hare algorithm", which is trivial to explain and code.
The catch?
It took a decade of computer science research between the original statement of the problem and Floyd discovering the solution.
So... no worries, you have an hour, a marker, and a whiteboard. Your time starts: now.
The tortoise and hare algorithm is not the foundational skill required to make software work the way an understanding of motion is for building structures. That's why it's often omitted from educational material yet these people are able to produce usable software after even something like a bootcamp (which I guarantee basically no bootcamps ever touched this algorithm).
I'm not sure I approve of asking even more well known algorithms like Djikstra's algorithm or A* in a job interview, unless the role was something that specifically required that area of knowledge like building pathfinders for video games or robots or something.
You’re expecting the mechanical engineer to recall something they learned about kinematics, not derive it on the spot. It’s a test of knowledge, rather than cleverness. The equations of motion are also more central to physics and engineering.
A decent programmer should know that linked lists exist, their general properties, pros and cons, etc. However, cycle detection is not a particularly common operation, so not knowing Floyd’s algorithm tells you very little—-and their failure to do years of research in 45 minutes even less.
Also, it took around 13.8 billion years for Newton to do what he did.
If they actually aren't looking for people who just cram CTCI or leetcode, coming to this answer from first principles is demonstrably far more difficult than you'd expect achieved in an interview.
These sort of questions have an incredible recency bias, and have zero relevance to engineering competence.
Of course; how else do you do back-door age discrimination?
"So we specifically asked for linear time."
"Uh, yeah, I did it in log(n). That's better."
"It doesn't match what's on this paper they gave me. Thanks for your time. We'll be in touch."
No such avail. In fact, unless these algorithms and problem solving methodologies are baked into your memory there's no way you are white boarding a Leetcode hard level problem in an interview.
What I was impressed at an Uber interview was their system design interview process - which basically boiled down to 'how do I abstract retrying a 429 - rate limit exceeded.
What I take is that - the interviewer is expecting a very specific solution even in an open ended system design question. It's like throwing a needle in a haystack at you and expect you to get to the needle in like an hour :).
They're probably looking for some sort of variable refilling leaky bucket implementation, which is funny because I believe this is exactly what they do internally. It was probably the task the interview had in front of them in their day-to-day and wanted you to do it for them!
This is a fair design question for a senior role (which this sounds like) that promotes disccussion, but expecting a specific solution is really only testing "does this person match my preconceived ideal for what a <dev> is?" which is really dangerous and has very little value.
I thought it was exactly those who Google wants to pass. Anecdote: ex-colleague of mine who is not specially bright studied 3 months how to "crack the coding interview" and got a job at Google. His knowledge about algorithms and data structures was like mine: I know what a tree is, I know there exists operations one can perform on them and some of them are more performant/efficient than others... but I would need to Google how to "reverse a binary tree" if I had to do it in less than 1h.
Plenty of times where I've used trees because they're the logical representation of the problem (ever had a field called "children" in your code? HN comments are a tree. Etc.)
Sounds bright to me.
I think your weights are way off.
The biggest difficulty for most seems to be that they don't know what "reverse a binary tree" actually means. It sounds kind of mathy and opaque, so I get it, but candidates should be able to have a dialog to figure out what the requirements mean. And on the flipside interviewers should be ready to have that dialog and not count not knowing the term by heart against the candidate.
This problem to me feels qualitatively different than the "rabbit and hare" algorithm for finding a loop in a linked list mentioned by another poster. That one needs a non-trivial algorithmic insight that just might not come to you during an interview. The solution to "reverse a binary tree" flows out of the structure of the problem statement as long as you have the fundamental skills for walking and manipulating data structures and the conversational skills to understand the problem, both of which seem fair to test for.
While it's probably not what an interviewer is looking for, having the most common solutions memorised gives you an advantage of time. A coding interview usually consists of two challenges. If you get stuck on the first one and take too much time to answer it, you won't have enough time to go through the second one.
To avoid the code printer perception you can always go through an explanation what alternative solutions could be applied to the given problem, what their complexities would be and why the one presented is the best.
And yet, they routinely do pass these interviews.
That's just absurd. If someone with no "algorithm" experience who was a good problem solver had to work out an answer from scratch for the interview its almost certain they're going to find the brute force answer and FAANGs pretty universally want the most efficient one so these people would routinely fail.
Its totally clear that what FAANG hiring optimizes for is recent CS graduates who passed tough Algorithm weed out courses at well known colleges in the past 18-24 months. They are young with no families or obligations and are happy to work 12 hour days at Google because they have hip open offices and ping pong tables.