4 ms·

What I'm not getting about these is the "don't cheat" bit. First, let's be clear: he's decided the 'rules' for this exam include not researching online or getti

by delinka 14y ago

What I'm not getting about these is the "don't cheat" bit. First, let's be clear: he's decided the 'rules' for this exam include not researching online or getting other assistance and just answering from memory. "Cheating" is "breaking the rules." I work in the Real World, where I don't write academic data structures every day, so I don't have this stuff memorized (there's a joke in there that start "I've forgotten more than...") I use APIs to get work done. When I need to be more academic, I search online. The only place anyone's ever required to be so 'academic' about algorithms, data structures, math, etc is in academia. Step out into a job and you have an internet of active developers and useful forums are your disposal. Even if a company hired me to write an 'academic' code library, I'd do the research, write the implementation, and (after sufficient testing, profiling, etc) forget about it.

cperciva 14y ago
What I'm not getting about these is the "don't cheat" bit If I said "go ahead and use google, wikipedia, textbooks, and talk to your friends", I would have needed to make the questions harder and lengthier to compensate. I thought asking people to spend 15 minutes telling me what they know would be more feasible than asking people to spent 15 hours showing me what they can find out.
- delinka 14y ago
  I understand. To gather data, you need manageable data. What will this data show you? What are you hoping to learn from this experiment? Perhaps I'm being a little cynical, but it seems to me that this information will tell you little about the craft outside of academia. P.S. I've refrained from answering the exam precisely because I'd have to refresh my memory from online resources.
- scott_s 14y ago
  Which is reasonable, since it's your time. But consider that I have three degrees in CS (BS, MS and PhD). I am employed doing CS research, primarily in systems and high performance computing. And for at least one question on each subject, I would not feel comfortable answering unless I referred to some reference. (Yes, even the architecture and systems questions, despite that being my "expertise": I can recall very little about coherence algorithms.) The primary value of a formal education is, I think, not that you know a lot of stuff. Rather, it's knowing what you don't know. Knowing just enough to recognize "Oh, this is related to that other thing, I should go and read about that." I'm constantly doing that, as are the people I work with.
tzs 14y ago
If you have to go to the net for basic things, you are going to be less productive than someone who is able to understand and use those things from memory, because of (1) the time it takes to find the information online, and (2) the interruption in flow. The majority of his problems were things that I'd say are in the "should be in memory" category for those who work in the general area that the particular question covers.
- jules 14y ago
  More importantly, you don't know what you don't know. If you don't have something in memory, even though that knowledge is readily available on the web, you probably won't notice an opportunity to apply that knowledge. That said, while I can answer these questions, they are pretty specialized knowledge. It's is a common phenomenon to think that the specialized area you work in is a big part of the world because you spend so much time in it. People should not feel bad about not knowing the answers to these questions. A web developer doesn't need to know any of these things, and he would be able to come up with web development questions that would be equally hard to answer if don't happen to be in that area (e.g. In which browsers is css-property-foo supported? or: what is faster, setting innerHTML or inserting a new elment into the DOM?). Even within the area of computer science, the author is asking specialized questions about hardware, security and algorithms. If it was about machine learning, type systems, and parsing you'd have a completely different set of questions. Or it could have been about computer graphics, compiler optimization, human computer interaction, and programming languages.
- delinka 14y ago
  "Why should a message be "padded" (and not just with zeroes) before being encrypted or signed using RSA?" I just happen to know this one. I know effective developers that don't. This is not 'basic' information. "What is the expected run-time of quicksort? What is the worst-case run-time?" Who cares? Call the sort method on your array class, call a sort function. Done. I don't need to know this for everyday things. "Name and describe the four states in MESI cache coherence." This is 'basic' knowledge? Maybe if I wrote a kernel in school, and if I did, I certainly don't remember the details of dealing with cache coherence 25 years later. I'm not a kernel developer now. Nor are a Very Large Percentage of developers in the real world. "Which of the following two functions is faster, and why? Assume that the C code is translated into machine code in the obvious manner, without optimization." Again, I just happen to know this one. But the "without optimization" almost makes the exercise silly. As your employer, I'd want to know you have the analytical skills to find the bottleneck in the code or to discover the compiler bug whose optimization is causing problems. "Explain the difference between a mutex and a read-write lock." Sorry, I'm using a higher-level construct. GCD from Apple, go routines in go ... do I 'fail' this question because I don't have to remember this from 15 years back?
alexkus 14y ago
The more you "know" the less you have to go look for, and when you do have to go look for stuff on the Internet (since you're not omniscient) then you'll understand more of the pages you get back as results, and understand them faster since there's less groundwork you need to cover. An understanding big-O notation is very important if you go searching for sorting algorithms and land on a page that has an overview of sorting functions but listing bogosort as O(n!) and insertion sort as O(n^2), both relatively easy to implement, and this relatively complicated iterative[1] quick sort that's listed as O(n log n). Without other clues someone might just implement the one that looks easiest, and it works fine on their test set of 20 elements, but blows up in the future as their application/site grows and slows to a crawl sorting through millions of rows with an insertion sort. Or, one of the most recent questions in the Mathematics part of the exam made me snigger because someone I work with was asking what bignum library was easiest to use. Rather than just answering their question (I prefer GMP myself) I asked why; they wanted to do the equivalent of log( x^300 ) and so they needed to compute x^300 first and then take the log of it; floating-point was giving slightly inaccurate answers to what was expected when they took the log of the intermediate result. It was even worse when they tried to do log( x^9125 ) - or whatever exponent is used for daily interest on a 25 year mortgage to account for leap days. To put it another way. Without the knowledge you end up googling, and implementing, the wrong thing. You may get the right answer/outcome in the end but it may be horribly inefficient. Or, worse, an inaccurate answer/outcome; and you may not even know. Hammering the insertion sort analogy home; you can profile and optimise an insertion sort all you like, it's still never going to approach the speed of quicksort on mid-large datasets. Huge datasets are another matter, someone stuck with "quicksort is the best" is going to struggle when faced with hundreds of millions of rows and there are things less pessimal than quicksort. Knowledge of processor architectures, caching and how hash tables are implemented means you know not to use a hash when a simple array will suffice; but I've seen this done plenty of times. Etc, etc, etc. Out of the 15 questions so far there's only been two or three that the knowledge of wouldn't have helped me at some point in my development over the last 15 years. Of those that haven't applied to me I can see why they would be important to other fields and other people. It's one of the major reasons I decided to do a full Maths degree (part-time via correspondence) to complement the Comp Sci degree I got ~15 years ago. It's not just the obvious useful stuff like calculus, group and set theory, graphs and networks, etc. Whilst I thought that the mechanics part of the Maths degree wouldn't be very useful in my job I was surprised at how useful and ubiquitous [non-]homogenous second-order linear differential equations are in modeling things that are relevant to my job (populations -> user base, hysteresis, etc). No doubt others find huge amounts of other knowledge in other subjects that is directly applicable to IT; psychology, education, design to name but a few. The right choice of algorithm, and implementation, in a critical part of your code could mean the difference between having 64GB of memory per server or getting by with 16GB. It could mean 100 servers to manage your 1M users, or 10 servers; the difference between 100 servers and 10 servers to manage your 1M users could mean the difference between making a profit and making a loss. These could be the differences between your idea succeeding or disappearing. 1. Another one of my common things I do at work is replacing quicksort implemented using recursion with an iterative version so that the stack doesn't keep getting blown on large datasets. I like it when people encounter this problem and find out that stacks are finitely sized and not as big as they'd hoped they would be. "But that means..." is a great thing to hear.

by delinka 14y ago

cperciva 14y ago

What I'm not getting about these is the "don't cheat" bit If I said "go ahead and use google, wikipedia, textbooks, and talk to your friends", I would have needed to make the questions harder and lengthier to compensate. I thought asking people to spend 15 minutes telling me what they know would be more feasible than asking people to spent 15 hours showing me what they can find out.

delinka 14y ago
I understand. To gather data, you need manageable data. What will this data show you? What are you hoping to learn from this experiment? Perhaps I'm being a little cynical, but it seems to me that this information will tell you little about the craft outside of academia. P.S. I've refrained from answering the exam precisely because I'd have to refresh my memory from online resources.
scott_s 14y ago
Which is reasonable, since it's your time. But consider that I have three degrees in CS (BS, MS and PhD). I am employed doing CS research, primarily in systems and high performance computing. And for at least one question on each subject, I would not feel comfortable answering unless I referred to some reference. (Yes, even the architecture and systems questions, despite that being my "expertise": I can recall very little about coherence algorithms.) The primary value of a formal education is, I think, not that you know a lot of stuff. Rather, it's knowing what you don't know. Knowing just enough to recognize "Oh, this is related to that other thing, I should go and read about that." I'm constantly doing that, as are the people I work with.

tzs 14y ago

If you have to go to the net for basic things, you are going to be less productive than someone who is able to understand and use those things from memory, because of (1) the time it takes to find the information online, and (2) the interruption in flow. The majority of his problems were things that I'd say are in the "should be in memory" category for those who work in the general area that the particular question covers.

jules 14y ago
More importantly, you don't know what you don't know. If you don't have something in memory, even though that knowledge is readily available on the web, you probably won't notice an opportunity to apply that knowledge. That said, while I can answer these questions, they are pretty specialized knowledge. It's is a common phenomenon to think that the specialized area you work in is a big part of the world because you spend so much time in it. People should not feel bad about not knowing the answers to these questions. A web developer doesn't need to know any of these things, and he would be able to come up with web development questions that would be equally hard to answer if don't happen to be in that area (e.g. In which browsers is css-property-foo supported? or: what is faster, setting innerHTML or inserting a new elment into the DOM?). Even within the area of computer science, the author is asking specialized questions about hardware, security and algorithms. If it was about machine learning, type systems, and parsing you'd have a completely different set of questions. Or it could have been about computer graphics, compiler optimization, human computer interaction, and programming languages.
delinka 14y ago
"Why should a message be "padded" (and not just with zeroes) before being encrypted or signed using RSA?" I just happen to know this one. I know effective developers that don't. This is not 'basic' information. "What is the expected run-time of quicksort? What is the worst-case run-time?" Who cares? Call the sort method on your array class, call a sort function. Done. I don't need to know this for everyday things. "Name and describe the four states in MESI cache coherence." This is 'basic' knowledge? Maybe if I wrote a kernel in school, and if I did, I certainly don't remember the details of dealing with cache coherence 25 years later. I'm not a kernel developer now. Nor are a Very Large Percentage of developers in the real world. "Which of the following two functions is faster, and why? Assume that the C code is translated into machine code in the obvious manner, without optimization." Again, I just happen to know this one. But the "without optimization" almost makes the exercise silly. As your employer, I'd want to know you have the analytical skills to find the bottleneck in the code or to discover the compiler bug whose optimization is causing problems. "Explain the difference between a mutex and a read-write lock." Sorry, I'm using a higher-level construct. GCD from Apple, go routines in go ... do I 'fail' this question because I don't have to remember this from 15 years back?

alexkus 14y ago

The more you "know" the less you have to go look for, and when you do have to go look for stuff on the Internet (since you're not omniscient) then you'll understand more of the pages you get back as results, and understand them faster since there's less groundwork you need to cover. An understanding big-O notation is very important if you go searching for sorting algorithms and land on a page that has an overview of sorting functions but listing bogosort as O(n!) and insertion sort as O(n^2), both relatively easy to implement, and this relatively complicated iterative[1] quick sort that's listed as O(n log n). Without other clues someone might just implement the one that looks easiest, and it works fine on their test set of 20 elements, but blows up in the future as their application/site grows and slows to a crawl sorting through millions of rows with an insertion sort. Or, one of the most recent questions in the Mathematics part of the exam made me snigger because someone I work with was asking what bignum library was easiest to use. Rather than just answering their question (I prefer GMP myself) I asked why; they wanted to do the equivalent of log( x^300 ) and so they needed to compute x^300 first and then take the log of it; floating-point was giving slightly inaccurate answers to what was expected when they took the log of the intermediate result. It was even worse when they tried to do log( x^9125 ) - or whatever exponent is used for daily interest on a 25 year mortgage to account for leap days. To put it another way. Without the knowledge you end up googling, and implementing, the wrong thing. You may get the right answer/outcome in the end but it may be horribly inefficient. Or, worse, an inaccurate answer/outcome; and you may not even know. Hammering the insertion sort analogy home; you can profile and optimise an insertion sort all you like, it's still never going to approach the speed of quicksort on mid-large datasets. Huge datasets are another matter, someone stuck with "quicksort is the best" is going to struggle when faced with hundreds of millions of rows and there are things less pessimal than quicksort. Knowledge of processor architectures, caching and how hash tables are implemented means you know not to use a hash when a simple array will suffice; but I've seen this done plenty of times. Etc, etc, etc. Out of the 15 questions so far there's only been two or three that the knowledge of wouldn't have helped me at some point in my development over the last 15 years. Of those that haven't applied to me I can see why they would be important to other fields and other people. It's one of the major reasons I decided to do a full Maths degree (part-time via correspondence) to complement the Comp Sci degree I got ~15 years ago. It's not just the obvious useful stuff like calculus, group and set theory, graphs and networks, etc. Whilst I thought that the mechanics part of the Maths degree wouldn't be very useful in my job I was surprised at how useful and ubiquitous [non-]homogenous second-order linear differential equations are in modeling things that are relevant to my job (populations -> user base, hysteresis, etc). No doubt others find huge amounts of other knowledge in other subjects that is directly applicable to IT; psychology, education, design to name but a few. The right choice of algorithm, and implementation, in a critical part of your code could mean the difference between having 64GB of memory per server or getting by with 16GB. It could mean 100 servers to manage your 1M users, or 10 servers; the difference between 100 servers and 10 servers to manage your 1M users could mean the difference between making a profit and making a loss. These could be the differences between your idea succeeding or disappearing. 1. Another one of my common things I do at work is replacing quicksort implemented using recursion with an iterative version so that the stack doesn't keep getting blown on large datasets. I like it when people encounter this problem and find out that stacks are finitely sized and not as big as they'd hoped they would be. "But that means..." is a great thing to hear.