Optimizing a breadth-first search (opens in new tab)

This was my thought too, but I don't want to assume: he cites enough standard but specific sources that he should know the general search algorithms. Also I think that since he doesn't mention standard depth first search at all it perhaps wasn't relevant?

The article is about optimizing the saved state information of the search, not about optimizing the search itself.

wow, I've thought about this for so long .. never would have found this wikipedia page on my own.

>Something has happened to Comp Sci programs over the past 3 decades. Based on what's too small a sample size (the graduates I've been interviewing in SF) it seems like a very large number of graduates from CS programs with 3.75 GPAs or above, can't do much more than glue together libraries, can't practically design a system on their own, and if ever confronted with a graph theory problem, can't do much more than name-drop algorithms, and fall far short of being able to implement those algorithms.

Ah, one of the pain points with companies in the Bay Area.

For the longest time one obvious, if not necessarily exclusive, problem with students who can achieve a 3.75 or higher GPA is that they tend to be much better at the rote memorization of concepts, but because they didn't necessarily "slog" through stuff, have some troubles, not try to just memorize formulas and algorithms, they don't have the ability to think through problems.

What about students in the 3.0 to 3.75 GPA range? Or are they considered "too dumb" to pass the resume filter you're using?

I think recruiting around here is targeted at "best and brightest" too much, and over-simplifies just the kind of people fit that qualifier.

I remember applying for internships while I was going to SJSU and many of the top companies in the area would have a drop down selection list of "which university did you attend?" and the list would only consist of the usual top UC's and top private schools.

I'm not saying actually smart people can't come from those universities, but when you're doing things like limiting a candidate search to 3.75 or greater GPAs, or filtering based on only "top" schools, then I think the issues you're describing are going to be much more immediate than otherwise.

I think you are using very rose colored glasses looking at the past. The best of the best could do that, likely. However, few could ever do things in seconds. Nor is there really any benefit in being able to solve something in seconds.

Interestingly, to me, it seems our industry was dominated by people that got good at gluing things together. To a very large degree. We bemoan this when we talk about how much more responsive machines used to be, but I think there can be very little denying that computers do more.

Granted, I suspect I am at best one of the bad graduates you are referencing. :(

> (the graduates I've been interviewing in SF) ... can't practically design a system on their own, and if ever confronted with a graph theory problem, can't do much more than name-drop algorithms, and fall far short of being able to implement those algorithms.

Interviewing people does not tell you the capabilities of people - interviews are very artificial processes.

I'm not exactly a computer scientist (or a recent graduate), but I work with tradeoffs every day, most of which are data derived, not problem derived & that is only visible from experiments on the data (sometimes across millions of ops).

However, what I really end up doing is actually different from just running experiments - I run the scale tests and go running while it runs.

I do my best thinking when I'm running - about a 10 minute mile pace in sunshine gives me my best ideas, perhaps it is a heart-rate thing.

And even when I have an idea, I will dig through researchgate for a couple of hours before I actually start pulling it apart (often, I find people have described the math which helps me think better) - like HyperLogLog used for IN() estimations.

Nobody's going to allow me to do any of those things in an interview.

Interviews are really about selecting people to hire, not about their abilities.

3.75 is a very high bar. I don't pass that bar. At that point I'd expect to be filtering work ethic much more strongly than skill or talent.

There may be some grads that have the problems that you describe but there are also many that have those skills. Look at the ICPC regional contests. Many students competing are very highly skilled in algorithms and hacking things together quickly. That does not always make them good employees.

I clicked on this thread to make a sure-to-be-downvoted ironic comment along the lines of "this isn't appropriate content for HN based on community sentiment regarding whiteboard interviews and what kind of work we actually do at our jobs."

There's a serious problem in the industry being driven by coding bootcamps; it's really sad to see universities being forced to stoop to compete.