Slashdot Mirror
What Programming Languages Should You Learn Next?
simoniker writes "Over at Dobbs Code Talk, Chris Diggins has been discussing programming languages beyond C++ or Java, suggesting options such as Ruby ('does a great job of showing how powerful a dynamic language can be, and leverages powerful ideas from Smalltalk, Perl, and Lisp') but suggesting Scala as a first choice ('Very accessible to programmers from different backgrounds.') What would your choice be for programmers extending beyond their normal boundaries?"
You're right that if you know one C-style language you know them all, and in order to expand your development skills you should learn other styles of languages. However, a major problem is that there aren't so many references for non-C-style languages as there are for C(++), Java, Python, and Ruby. Though Lisp is something all developers should encounter, most Lisp books on the market are antiquated. (However, thank goodness for the relatively modern Practical Common Lisp by Seibel.) I wish there were more tutorials out there for the exotic languages that might really teach you new tricks.
Verilog is a hardware description language, not a programming language. It may look like a high-level language -- wire assignments look like variable assignments, module instantiations look like function calls -- but conceptually it's completely different. Furthermore I don't know how applicable it's going to be for anyone who works in software design, which is the audience this question seems geared towards.
Functional languages seek to express all operations as a chain of functions which operate on data and return other data. "Function" is used in its mathematical sense here. Purely functional languages discourage state, and don't allow mutable variables. The lack of state and mutability give rise to some power; effortless parallelizability, for instance.
Logic languages are something different altogether. They provide a framework for defining the rules of a system, then searching for answers which fit the given rules. Logic programming is not useful for general-purpose tasks, but can hugely reduce programming time in tasks which are difficult to solve any other way.
Cretin - a powerful and flexible CD reencoder
It's a programming language for programming a type of CPU called an FPGA.
It's not. It's a hardware description language, so can be used in FPGAs, but is equally used for ASIC designs.
Furthermore, an FPGA is NOT a CPU of any kind. It's a configurable logic chip. You could program it as a CPU, but it's not one until you do.
If you're looking for books on LISP, another book to consider is On Lisp. It's free to download from the following link as it's inexplicably out of print.
http://www.paulgraham.com/onlisptext.html
And a powerful macro system. Scheme's is interesting, and you can do most anything with it, but certain things require a great deal of hoop-jumping.
Aside from conditions and restarts, macros seem like the last thing that hasn't sneaked into popular languages yet. For the uninitiated: imagine being able to write a function that, at compile time, takes and returns entire syntax trees. Or imagine if the C preprocessor let you write #defines that were full-fledged functions that had the entire language and runtime available during expansion.
Imagine if C let you hook into the tokenizer and the parser! Why, you could invent your own language for solving your problem, and then solve your problem in that language!
It's worth learning Common Lisp just to play with this stuff.
I got my Linux laptop at System76.
Just to make this a little more clear for the practical minded: the end result can be learning JML, a language that allows for annotations to Java (such as pre- and post-conditions for methods, assignability clauses for private variables, etc.). What benefit does that get you? Well you can use ESC/Java2 to run a theorem prover over those assertions about how things are supposed to work to verify that you code will actually meet all the claims you make of it (which is great for catching subtle unlooked for conrner cases). You can use the jmlunit tool from JML itself to create an automated set of unit tests to exercise you code against your annotations, and you also get (via jmldoc) to have your requirement annotations automatically included in your javadoc api documentation. When you consider that, for a lot of code, you ought to be writing those methods requirements up in api documentation anyway, all the extra extremely rigorous (and static/compile time) checking is just gravy. So there is plenty of practical benefit that's easy to get. To make best use of it, of course, you do need to have some grounding in how this sort of thing works so you can write your specifications well (no different, in many ways, than having some grounding in how CPUs work so you can write more efficient code).
Craft Beer Programming T-shirts