I love discussing the manhole question because the alleged answer is not the point. The point of such a question is for the candidate to think aloud and walk you through their problem exploration process. Such questions select for people who are a little meta about themselves, which is why they can think about something and talk about their thinking at the same time.
But that really illustrates the trap of almost all interview questions. The interviewer is obsessed with the correct answer, when in reality it's the process of arriving at any answer that matters.
My personal beef with "Aha!" questions is that if given one that I actually solve on the spot, I can't tell you much about how I got it. It just came to me.
The only exception I can remember is a question about finding whether a linked list has a cycle in it. The "proper" answer involves a pair of cursors, one of which operates at double the speed of the other. I came up with a much less efficient but equivalent solution because the problem reminded me of something we did with Turing machines in college back in the 80s.
So in that particular case I could actually explain how I arrived at an answer. Now that I think about it, I think I'm a pattern-matching machine. My algorithm for solving problems is to perturb them until they resemble something I've seen before.
The infamous retort is this parody: http://hebig.org/blogs/archives/main/000962.php
But that really illustrates the trap of almost all interview questions. The interviewer is obsessed with the correct answer, when in reality it's the process of arriving at any answer that matters.
My personal beef with "Aha!" questions is that if given one that I actually solve on the spot, I can't tell you much about how I got it. It just came to me.
The only exception I can remember is a question about finding whether a linked list has a cycle in it. The "proper" answer involves a pair of cursors, one of which operates at double the speed of the other. I came up with a much less efficient but equivalent solution because the problem reminded me of something we did with Turing machines in college back in the 80s.
So in that particular case I could actually explain how I arrived at an answer. Now that I think about it, I think I'm a pattern-matching machine. My algorithm for solving problems is to perturb them until they resemble something I've seen before.