Notes on Data Structures and Programming Techniques
cs.yale.edu
cs.yale.edu
Seems reasonable to me. We learn math by doing by hand, so we can understand the whys and how’s. This doc (and course), correctly or not, draws the same parallel with C.
I definitely agree, but I'm not sure that a data structures/algorithms course is the best place to be teaching that. I don't know anything about Yale's CS curriculum, but I'd hope there's at least one systems programming course in there.
Like to mention this is with Java, and not C.
http://cs.yale.edu/homes/aspnes/classes/223/notes.html#What....
7.1 What's wrong with C
a) C doesn't have a garbage collector
Disagree that's it's wrong. If you code is well structured, then it's no big problem to avoid memory leaks. On top of that, you can use RAII if you are willing to use C-extensions like this one:
https://lwn.net/Articles/589433/
Garbage collector just helps you to write semi-workable messy code (a dream of industrial developers).
b) C doesn't support any kind of polymorphism
If you use type cast in well structured code, it's no big problem.
c) C doesn't have exceptions
This may be a bit tricky but you still can use exceptions in C using longjmp/setjmp:
http://www.di.unipi.it/~nids/docs/longjump_try_trow_catch.ht...
Although __cleanup__ extension doesn't work in this case.
It's worth to take a look at this stack unwinding library:
http://www.nongnu.org/libunwind/
Quote:
With libunwind, it is possible to implement an extremely efficient version of setjmp(). Effectively, the only context that needs to be saved consists of the stack-pointer(s).
In general, if you look at C as a high level assembler and willing to write or use existing low-level framework for "meta-language" primitives (like pointer virtualization), then you can write nice programs in your "meta-language".
For example, I wrote some project for fun using pure C with bare minimum libraries. And I needed to make sure that I could detect the following bug as soon as possible:
1. Object X is created and owned by some code OWNER_X;
2. Pointer to this object X is passed to some code USER_OF_X;
3. Object X is freed in OWNER_X;
4. New object Y is created in OWNER_X which happens to have the same address as recently freed object X;
5. Because of some bug USER_OF_X still uses pointer to object X;
I wanted USER_OF_X to fail on asserts as soon as possible if this happens. It would be hasty bug and hard to detect in unprepared code if X and Y happens to be the same type. When people are saying that it's nearly impossible to detect such bugs in C, they just don't consider using framework which cleverly detects this issue.
By the way, this is my implementation pointer virtualization which helps to detect this sorts of bugs:
https://github.com/hal9000xp/euclid/blob/master/core/main.h
Look at PTRID.
https://github.com/hal9000xp/euclid/blob/master/core/linked_...
Look at usage of PTRID in LL_CHECK
This is how I use them together:
https://github.com/hal9000xp/euclid/blob/master/core/network...
Found a small issue. In Binary search section, it says ```{.c include=examples/binarySearch/binarySearch.h}```
Instead of the original code. I guess the page generator messed up a little.
I’m on an iPad, fwiw. Ironically one that usually gets some of the worst styling due to someone else’s opinion of readable.
Or more realistically, taking a more layered approach to each course. So you could have the basic "code algorithm X to pass the tests" level (the kind of work most people will be doing later anyway), and then the "let's prove properties of X / come up with an alternative with the same properties" for people who can pass the first part in their sleep.
The best courses I've taken work like that already, plenty of extra challenges if you finish early. But it takes a dedicated instructor to make it work, and most of them unfortunately seem dedicated to getting by with minimum effort.
For instance, I recall my professor being wired up about some esoteric sorting algorithm, that had better asymptotic performance than qsort. Except, the constant factors involved in a real implementation made it slower for anything but stupidly big datasets. We spent like a week going over that one...
I ask because data structures usually comes in the 2nd or 3rd semester of a CS curriculum, and for most CS students, they can't apply the proofs and theory because it obscures where it applies in the problem domain. They can't draw the line between the theory and practical application, unless they already have written a good bit of code.
Maybe this doesn't apply to all CS students, but I would say the majority.
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