Regarding C) No. Definately not (IMO anyway). Did the fact that I implemented 2-3 trees (aka red-black trees) in perl rob me of understanding 2-3 trees? Did it with huffman compression? Did it with LZW compression? Treaps? No no, perl frees you from all the BS junk and allows you to narrow down quickly on the algorithm at hand. It may not be as efficient as the same thing coded in C, but its the same algotihm and thus will perform just the same way.
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demerphq
First they ignore you, then they laugh at you, then they fight you, then you win.
-- Gandhi
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Definitely yes -- if you are avoiding the intracies of pointer manipulation. True that trees as such can be aided by higher level languages, but there is nuance and skill learned in finer manipulation (though it be drudgery) that will allow you to perform far greater things in other languages when Perl is not always available.
Don't do your data structures work in Perl if you want to really get something from the class. If you are just trying to avoid drudgery, well yeah, Perl helps. But do it ground up at least once, and you'll come out a changed developer.
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Well, I learned and programmed in a lot of other languages before I came to Perl so Im aware of the differences. Pascal in particular... *shiver* But anyway, I dont know that I agree with your last point. Personally amongst the first thing I do with a new language is write certain data structure implementations. Try 2-3 trees in VB. Blech. :-) Perl has a natural slant and thus some algorithms work nicely in Perl, others go against the grain as it were and are actually far less efficient than they should be. But aside from that if you learn an algorithm in a language like perl then you probably havent had to deal with as much language and representation specific gunk so you have probably learned the core ideas better. So when you go to implement in another language you're more free of language specific distractions and can concentrate on figuring out how to implement the core behaviour, not the equivelent of the other implementation you wrote.
For instance
sub build_huffman_tree {
my $input=shift;
my %count;
$count{$_}++ for split //,$input;
my @list=map { [ $_, $count{$_} ] } keys %count;
while (@list>1) {
@list=sort {$a->[1] <=> $b->[1]} @list;
my ($x,$y)=splice @list,0,2;
push @list,[[$x,$y],$x->[1]+$y->[1]];
}
return wantarray ? @list : $list[0];
}
The equivelent code in almost any other language would be much larger, and would do no better, and IMO signifigantly worse at illustrating the ideas behind Huffman encoding. Optimising this so that it only calls sort once for instance only detract from the core idea of the algorithm.
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demerphq
First they ignore you, then they laugh at you, then they fight you, then you win.
-- Gandhi
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C? Bah!, that's making it too easy. Write algorithms in MIX, the way God and Knuth intended it!
More seriously, perl is an excellent language for learning algorithms. One can get to the crux of the algorithm without fussing with memory management and other low-level irritations. The resulting simpler, cleaner code allows one to see what is going on. And the elimination of a separate compile step allows one to play with code in a more exploratory, interactive fashion. The book
Mastering Algorithms with Perl is a fine example of how fun and easy learning algorithms can be.
I also think that having a hash as a fundamental part of the language makes a big difference in the ease of designing and implementing algorithms. Set operations become simple, as do tree and graph algorithms. There was an interesting study by Lutz Prechelt comparing programming efficiency across a wide range of languages. In it there was a text-processing task that was a natural for hashes. Despite both languages having hashes available through libraries, the C++ and Java folks tended to instead write huge amounts of code implementing n-ary trees, etc. instead of taking the easy way. Unless speed or memory limitations prevent it, it is generally a good idea to use the high-level tools you you have at hand.
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