6 ms·

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 see

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. There are literally problems that were 1) once covered in freshman year, 2) could once be recognized and solved by CS grads in seconds, 3) stump recent CS graduates, 4) prompt HN commenters to say how they could solve it if given a few days, and 5) come up in conversation if you go to meetups and talk to people doing actual work. How does this relate to BFS? It used to be that someone trained as a computer scientist would look at a data structure or a graph and start running some quick gedankenexperiments: What would happen if I tried to find that with DFS? What would happen if I tried to find that with BFS? Those aren't going to be suitable solutions for all problems, but it's a good place to start thinking. There seem to be a large number of recent grads who can't even get that far.

hashkb 8y ago
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.
- duxup 8y ago
  "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." Is that really the case, universities are trying to compete with bootcamps? I don't see much in the way of signs of that.
taeric 8y ago
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. :(
- hashkb 8y ago
  Nobody here would deny the business value of gluing APIs together. We're not asking for your empathy, either; but we are telling you the truth about the difference between where the bar was and where it is now. The idea that "computers are fast, my code just needs to work" is a really really horrible way to treat your users' devices. A whole host of similar ideas are now popular, and it's pretty obvious that it's because the industry is now dominated by people that are (just) good at gluing things together. This is a bad thing.
  - taeric 8y ago
    I'd wager the bar wasn't as high back then as you think. Most people still wrote inefficient things. Lots of it. There is a hope that most of the inefficient things flat out stalled out due to needing to be much more frugal of resources, but I don't know of any data backing that. So, seriously, do you have data showing that the bar is lower? Or are you just performing selection and survivor bias to get such a negative view? (Similarly, am I doing the same to get a positive view?) My main qualm is people that seem to hold incoming folks to the bar that they have today, without acknowledging the growth that was necessary for some of that. As a parent, I fully know my children will be better at most everything than I am. In time. Same for most of the younger generation coming out of college into the industry. Most are or will be better than I am. Pretty much full stop.
    - stcredzero 8y ago
spike021 8y ago
>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.
- stcredzero 8y ago
  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 http://v.cx/2010/04/feynman-brazil-education http://v.cx/2010/04/feynman-brazil-education
  - spike021 8y ago
    Wow, this article tells a pretty incredible story. Thanks for sharing! It definitely echoes exactly what I was thinking about.
ball_of_lint 8y ago
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.
- stcredzero 8y ago
  3.75 is a very high bar. https://www.pbs.org/newshour/economy/column-how-an-epidemic-of-grade-inflation-made-as-average https://www.pbs.org/newshour/economy/column-how-an-epidemic-...
gopalv 8y ago
> (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.
- stcredzero 8y ago
  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). I don't think I'd know how to interview someone for your position. I do my best thinking when I'm running I've had similar experiences. Of course I'm not possessed by the idea that interviews are very good as a general mechanism. I've given allowances for nervousness and pressure. I certainly know what it's like to be on the other side of the table. Even allowing for all of those things, it leaves me wondering.

hashkb 8y ago

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.

duxup 8y ago
"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." Is that really the case, universities are trying to compete with bootcamps? I don't see much in the way of signs of that.

taeric 8y ago

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. :(

hashkb 8y ago
Nobody here would deny the business value of gluing APIs together. We're not asking for your empathy, either; but we are telling you the truth about the difference between where the bar was and where it is now. The idea that "computers are fast, my code just needs to work" is a really really horrible way to treat your users' devices. A whole host of similar ideas are now popular, and it's pretty obvious that it's because the industry is now dominated by people that are (just) good at gluing things together. This is a bad thing.
- taeric 8y ago
  I'd wager the bar wasn't as high back then as you think. Most people still wrote inefficient things. Lots of it. There is a hope that most of the inefficient things flat out stalled out due to needing to be much more frugal of resources, but I don't know of any data backing that. So, seriously, do you have data showing that the bar is lower? Or are you just performing selection and survivor bias to get such a negative view? (Similarly, am I doing the same to get a positive view?) My main qualm is people that seem to hold incoming folks to the bar that they have today, without acknowledging the growth that was necessary for some of that. As a parent, I fully know my children will be better at most everything than I am. In time. Same for most of the younger generation coming out of college into the industry. Most are or will be better than I am. Pretty much full stop.
  - stcredzero 8y ago

spike021 8y ago

>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.

stcredzero 8y ago
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 http://v.cx/2010/04/feynman-brazil-education http://v.cx/2010/04/feynman-brazil-education
- spike021 8y ago
  Wow, this article tells a pretty incredible story. Thanks for sharing! It definitely echoes exactly what I was thinking about.

ball_of_lint 8y ago

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.

stcredzero 8y ago
3.75 is a very high bar. https://www.pbs.org/newshour/economy/column-how-an-epidemic-of-grade-inflation-made-as-average https://www.pbs.org/newshour/economy/column-how-an-epidemic-...

gopalv 8y ago

> (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.

stcredzero 8y ago
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). I don't think I'd know how to interview someone for your position. I do my best thinking when I'm running I've had similar experiences. Of course I'm not possessed by the idea that interviews are very good as a general mechanism. I've given allowances for nervousness and pressure. I certainly know what it's like to be on the other side of the table. Even allowing for all of those things, it leaves me wondering.