Should CS students be graded on performance?
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Should CS students be graded on performance?
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Re: Should CS students be graded on performance?
#2It depends on the context of the problem:
* If it's being framed as being applied to a small number of items on one machine, I'd mark down for premature optimization. Normally such assignments have a specific point, and going off the deep end with efficiency measuring often misses it.
* If it's being framed as being applied to huge data sets, asymptotic complexity is the metric to go off of.
* If it's being framed as a latency-dependent (UI, servers) then actual timing is the metric to grade off of.
I'd say that if you have an algo that is faster for small numbers, it usually doesn't really matter that it's faster. Small numbers go fast no matter what. Unless it's latency dependent, it's encouraging students to work on things that don't matter at all.
EDIT: spacing EDIT2: spelling
Re: Should CS students be graded on performance?
#3It depends on the context of the problem: * If it's being framed as being applied to a small number of items on one machine, I'd mark down for premature optimization. Normally such assignments have a specific point, and going off the deep end with efficiency measuring often misses it. * If it's being framed as being applied to huge data sets, asymptotic complexity is the metric to go off of. * If it's being framed as…
When you were in class, where you ever even introduced to the concept that sometimes it might be possible that O() notation might not tell the whole truth? I understand that for the most part you shouldn't have to worry about it, but shouldn't we still warn students about this?
Re: Should CS students be graded on performance?
#4It depends on the context of the problem: * If it's being framed as being applied to a small number of items on one machine, I'd mark down for premature optimization. Normally such assignments have a specific point, and going off the deep end with efficiency measuring often misses it. * If it's being framed as being applied to huge data sets, asymptotic complexity is the metric to go off of. * If it's being framed as…
When you were in class, where you ever even introduced to the concept that sometimes it might be possible that O() notation might not tell the whole truth? I understand that for the most part you shouldn't have to worry about it, but shouldn't we still warn students about this?
Do you mean something like the case of quicksort mentioned in the post?[1] I was taught average- and best-case analysis along with worst-case analysis. Or do you mean some other fact not revealed by that analysis?
[1] "Quicksort is a magical algorithm that theory tells us runs in O(n^2)"
Re: Should CS students be graded on performance?
#5It depends on the context of the problem: * If it's being framed as being applied to a small number of items on one machine, I'd mark down for premature optimization. Normally such assignments have a specific point, and going off the deep end with efficiency measuring often misses it. * If it's being framed as being applied to huge data sets, asymptotic complexity is the metric to go off of. * If it's being framed as…
When you were in class, where you ever even introduced to the concept that sometimes it might be possible that O() notation might not tell the whole truth? I understand that for the most part you shouldn't have to worry about it, but shouldn't we still warn students about this?
Could you explain what you mean a bit more by big O notation not telling the whole truth? Are you referring to the fact that algorithms that look the same in big O notation might have drastically different constants, which can affect real-world performance?
Re: Should CS students be graded on performance?
#6It depends on the context of the problem: * If it's being framed as being applied to a small number of items on one machine, I'd mark down for premature optimization. Normally such assignments have a specific point, and going off the deep end with efficiency measuring often misses it. * If it's being framed as being applied to huge data sets, asymptotic complexity is the metric to go off of. * If it's being framed as…
When you were in class, where you ever even introduced to the concept that sometimes it might be possible that O() notation might not tell the whole truth? I understand that for the most part you shouldn't have to worry about it, but shouldn't we still warn students about this?
Absolutely! I suppose when I speak of asymptotic analysis, I'm including average case/expected case/degenerate case analysis in the whole exercise. Perhaps "runtime analysis" is a better term - it can then incorporate latency analysis as well.
But yes, that was integal to the treatment of the subject. I remember having to determine what the worst-case of quicksort looks like as a part of an assignment to exhibit, in practice, best/average/worst case runtime of a number of sorts - and this was an freshman-level intro course. That particular problem was one of the most fun homeworks I've ever had - a rather satisfying solution.
Re: Should CS students be graded on performance?
#7First, find a better color scheme for something you intend people to read. That was painful.
Second, when I was a CS student I expected to be graded on my response to a particular problem. If you wanted me to roll my own sort, I expect that to be specified. If you want me to explain in comments why I chose certain algorithms say something in class. I'm not going to waste time implementing an efficient sorting algorithm for a 100 element list (or 1000 even) just to provide a TA with a nerdgasm.
I feel this article is asking if students should be graded on an arbitrarily deep rubric. I had enough to worry about as an undergrad without caring if a bored TA was going to dock me 10 points for calling Arrays.sort.
Re: Should CS students be graded on performance?
#8First, find a better color scheme for something you intend people to read. That was painful. Second, when I was a CS student I expected to be graded on my response to a particular problem. If you wanted me to roll my own sort, I expect that to be specified. If you want me to explain in comments why I chose certain algorithms say something in class. I'm not going to waste time implementing an efficient sorting algorit…
Will do for the color scheme.
What I was trying to ask was: Should real world performance be more heavily weighed? I feel like right now all the CS curriculum focuses on is O() performance as the end all.
Re: Should CS students be graded on performance?
#9Earlier quoted context omitted.
When you were in class, where you ever even introduced to the concept that sometimes it might be possible that O() notation might not tell the whole truth? I understand that for the most part you shouldn't have to worry about it, but shouldn't we still warn students about this?
Could you explain what you mean a bit more by big O notation not telling the whole truth? Are you referring to the fact that algorithms that look the same in big O notation might have drastically different constants, which can affect real-world performance?
Yes, that's exactly what I'm getting at. Or cases where multithreading an application may look like it's going to bring obvious performance gain only to see the overhead kill your performance.
Re: Should CS students be graded on performance?
#10First, find a better color scheme for something you intend people to read. That was painful. Second, when I was a CS student I expected to be graded on my response to a particular problem. If you wanted me to roll my own sort, I expect that to be specified. If you want me to explain in comments why I chose certain algorithms say something in class. I'm not going to waste time implementing an efficient sorting algorit…
First, find a better color scheme for something you intend people to read. That was painful.