[eli_gottlieb]

Yes, but the algorithms relevant to a domain are not Algorithms 1&2 class algorithms. For example, writing a network protocol requires knowledge of finite-state machines, writing a type-inference engine requires knowledge of unification, writing a thread scheduler requires knowledge of various scheduling algorithms.

Knowing the most efficient way to find all the anagrams in a text is not relevant to any of them, though. And yes, I was given that problem in an interview last week. I got it right, but the actual position involved more knowledge of architecture, assembly, and compilation than of Algorithms Guru Yoga.

[DannyBee]

Well, I hope you weren't asked that at Google , since it's a banned question. If you were, let me know privately :)

I assume you understand the goal of these questions is not to figure out if you can perform memorization of algorithms 1 + 2, but to understand how you think about problems and watch you do it?

Note that, at least at Google, they still try to hire generalists (in most cases), so you would still get that "kind" of question there, even for a job involving architecture and assembly. This is a deliberate choice.

Of course, i'm sure you also realize that a lot of the algorithms in "architecture, assembly, and compilation" were developed by people who started out more as "Algorithms Guru Yoga" folks.

Gregory Chaitan, who developed Graph Coloring for register allocation, was definitely not a compiler guy

Only half the folks on the original conference paper for Static Single Assignment form for compilers were compiler people actually trying to solve that problem.

Robert Tarjan was not a compiler guy, but his scheme for computing dominators is still the main one used today, and his union-find algorithms (he also proved the upper bound on the already-known versions) are what are used for a lot of type unification algorithms.

The list goes on of "Algorithms Guru Yoga" folks who came up with the premiere solutions to problems in the field you are talking about.

So when you say "novel solutions require actual domain knowledge rather than an n-levels-deep memorization of the entirety of your Algorithms 1 and 2 courses from university.", it's a bit hard to take that seriously.

Novel solutions require both domain level knowledge, and the understanding you learned in Algorithms 1 and 2. Even the question you got about anagrams does not require any n-level wrote memorization. It requires only the most basic understanding of data structures, and an understanding of how to design algorithms.

[bcoates]

Why was it banned?

[DannyBee]

Because this one is very widely known, shows up in books on interviewing at google, etc, so it fails to be a question that is useful for evaluating anymore.

[eli_gottlieb]

At the very least, I can assure you it wasn't Google asking that question. It was, however, a well-known BigCo who employ quite a lot of software engineers and are generally known as the best at what they do.

Now, in answer to the rest of your post: you are broadly overestimating the curriculum of Algorithms 1 & 2. That is, Algorithms 1 & 2 + knowing you need to allocate registers is not going to necessarily lead you to graph coloring.

I assume you understand the goal of these questions is not to figure out if you can perform memorization of algorithms 1 + 2, but to understand how you think about problems and watch you do it?

I have heard this explanation; I simply don't see the evidence as in its favor. Basically, if you were looking for real problem-solving skill, you would have to entirely abandon the 45-minute interview format, whether it's on the phone or in-person.

That is, real problem-solving, as I've seen it and done it, tends to involve some kind of real problem domain (so you know what sort of solution is desirable), a real resource allocation (so you know what performance trade-offs to make), a less "academic exam" set-up (so you can experiment with solutions and see how they look), and more time to think than 20-35 minutes.

Interview environments are: relatively domainless, have no set resource allocation constraints other than "do well at Big-O performance measures", come as "pass/fail tests" rather than collaborative solving efforts, and are given with heavy time-pressure.

"My normal methods are useless here" -- those being to sketch out many solutions in a notebook over a period of hours or even days. Worse: the effect is almost to punish people who've had the audacity to spend significant portions of our careers in specific domains, from web-dev to type theory.

Also worse: interviewers tend to be unsatisfied until given their favored solution to their chosen question. In the example cited above, my interviewer was unhappy with my choice of a hash-table for a key-value store and actually asked me to go back and redo the problem "without using preexisting data structures". He ended up happy (I was called to do a second interview) when I told him we could make an insertion-sorted linked list of key-value mappings.

Why didn't I think of that in the first place? Because an insertion-sorted linked list performs worse than a hash-table as a key-value mapping data structure. A hash-table is, as far as I know, writing calmly and without pressure, the go-to key-value map for real programming. But most interviewers I've met are somewhat disappointed at seeing a hash-table, because using low-level data structures from the standard library is what stupid people do. Of course, it's also what experienced working programmers do.

Again, this one wasn't at Google, but it's a fairly good example of how BigCo interviewers come off as trying to play a round of Who's Mister Clever? more than actually engage in a problem-solving process. Other favored tactics include dinging you for what programming language you use, or questioning the syntax of your white-boarded code (had this happen to me in the same interview, turned out I was right when we asked one of the interviewer's colleagues).