Getting started with Tcl TK? [closed] - tcl

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One of my modules at university next year is going to involve programming in Tcl tk, I was wondering where to find the best resources and information about the language, so that I am well prepared. I'm currently looking on this site which is pretty helpful, but the book that they recommend is quite old, and I was wondering if someone could recommend any other books to purchase or if the language hasn't changed significantly since the release of the book in 1999?
Also, what projects or examples should I start working on to make me familiar with the language?
Any other information would be extremely helpful and appreciated!
I posted this question because I couldn't find any others similar too it, apologies if I haven't looked hard enough.
Thanks in advance,

Some of the books I have in my library that you might find useful are:
Tcl and the Tk Toolkit (Ousterhout) - The book on Tcl/Tk, and probably the one you're referring to. It's old and some of the information is a bit out-dated, but it is fantastic (and, I believe, I say that without exaggerating) at showing how to program in Tcl. It was written by the originator of the language.
Practical Programming in Tcl and Tk (Welch) - The other book on Tcl/Tk that nearly everyone that programs in it seriously has in their library. Brent did an amazing job on this book.
Effective Tcl/Tk Programming: Writing Better Programs with Tcl and Tk (Harrison, McLennon) - Once you get to larger, more complex, programs, this book can be very handy to have read. It goes into organization and the like. This book is likely beyond what you need at the moment, but I mention it because it's a very good read as you get deeper into Tcl.
It's also worth bookmarking the Tcler's Wiki. It can feel a bit unorganized at times, but there's more information there than... well, anywhere. It's an amazing resource.
The ActiveTcl distribution is, indeed the way to go. The folks over at ActiveState are a smart bunch.

Are you familiar with the Active Tcl distribution? If not, then this is the best place to start looking for resources and documentation.

You can also try TclTutor interactive application where you can not only learn the materail but also try it at once.

I also recommend Tcl and the Tk Toolkit. It is great for understanding the core of Tcl, though I can't comment on how useful it is as a reference (I use the online documentation for that). The second edition of Tcl and the Tk Toolkit is currently available as a "Rough Cut" from Safari Books Online (meaning that you can download a draft PDF now and a final PDF when the book is released). They seem to have added a bunch of information about Tk, especially the themed widgets that were introduced in 8.5. They also added some information to the section about Tcl, including dictionaries.

but the book that they recommend is quite old,
The fact about tcl is, it is quite old, the book by Ousterhout is still the best book on tcl (and IMHO, almost a classic). There was never even a second edition although one is apparently in the making. tcl was a great idea at the time and it doesn't really hurt to learn it, but it hasn't kept up and frankly had a lot of design issues from the start.
Don't get me wrong, I was a huge fan of tcl back in the day, but it's not the best thing to be learning now. If you decide to carry-on, pick up a used copy of the original book and use the online resources.
The original purpose of tcl was to be easy and free enough to eliminate the need for the myriad of home-grown command languages that folks were writing to add interactivity to their applications. Later, the Tk toolkit was added and it was the easiest, free way to add a GUI to an application.
Today, there are a lot more options available (for example for GUI's the Qt toolkit is now under the LGPL therefore almost as free at Tk.
For adding a command line interface to an existing C / C++ application, the closest modern tool is Lua, but even more powerful languages like ruby and python are not much harder to integrate with C/ C++ applications (especially with tools like boost python and SWIG).

An second edition of Ousterhout's book, updated and augmented by Ken Jones, is available. It has a release year of 2010, so the second edition is pretty current. Also, the wiki page http://wiki.tcl.tk/57 has a list of a number of books that deal with Tcl in some capacity.

Use this invaluable reference guide or this more up-to-date quick ref (thanks to Colin Macleod).

Able to program in Tcl may not land you a job, but it certainly can help you to get the work done fast. I learned Tcl back in 1996 and Tcl is still one of my favorite programming languages in solving most of my daily sys admin work. In most cases, I am able to accomplish the same task when my programming colleagues are still on the drawing board designing the object classes.

Besides from the great suggestions from other comments, I just have to add Tcl for Web Nerd by Philip Greenspun, the creator of the Tcl-based framework ACS (which later became OpenACS).

There is plenty of information on the Tcl Wiki, though it can be hard to find things. A look at the Recent Changes page will show that there's plenty of activity going on.

I have learnt it through Practical Programming in TCL/TK. It is a very good. Along with that TCL-TK toolkit book was also very helpful.

The most recent book I know of is Clif Flynt's Tcl/Tk: a developer's guide. The third edition was published in 2012 by Morgan Kaufman and it covers the (as I'm writing this answer) current version of Tcl: 8.6.
I've only had the book in my house for a week, but it looks to be quite thorough and I like what I've read so far.
I own and have read both Ousterhout's Tcl and the Tk Toolkit and Welch's Practical Programming in Tcl and Tk (2nd Ed) and I liked them both. But Tcl seems to have come a long way since my copy of Welch's was published and a very long way since Ousterhout's. There are some really important/nice things that have been added to the core language/library.
(Incidentally, I also thought the new paperback price was extremely reasonable on Amazon for an almost 800 page tome.)

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tips for learning from opensource [closed]

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Besides practice(practice and more practice) reading books and forums, analyzing others people code is a must in order to have a career in this field.
The problem is that I'm a student(feels like always on learning stage) but sometimes i can't solve the problems by my own. I was thinking that on public open source repositories might be the answer I'm looking for.
My question is how can i find the answer to some of my problems in open source projects/community? Do you have any tips to share for me?
ty
A few things for learning problem solving skills related to software developement (once you've found a project that you are interested in that is also written in a language you feel comfortable with) are:
Sign up to the mailing list
Lurk about on the project's IRC
channel (assuming they have one)
Read through bug repots (the open
ones to try solve them, and the
closed ones to see how others solved
them).
and of course discuss discuss discuss, if you think you have a basic grasp of the problem at hand but need clarification on some issues don't be afraid to ask your peers.
Hope this was of at least some help,
Welcome to the open source world and good luck!
Analyzing others people code is a must... I'm a student... public open source repositories might be the answer?
The problem with open source is that the quality varies too much.
(There's lots of my own code sitting in public open-source repositories that I wouldn't want anyone to try to see, let alone learn from.
And yet some of my code, the code I have lavished time and attention on, is very good—or so my peers tell me.)
So you don't want to pick an open-source project and learn from J. Random Hacker. You want to learn from the best hackers.
Here are some strategies:
If you're a student, you have acccess to teachers. One or two of them may have an idea about software. Ask them what is worth reading—what you will learn from.
Look at conferences and journals that publish about software: SIGPLAN, SIGSOFT, USENIX, Software—Practice & Experience, Journal of Functional Programming. Read about systems that look interesting to you. Write to the authors and ask them if they recommend you try to learn from their code. Listen carefully to what they say; most of the best hackers know they can do better. If you extract a grudging admission, with a bunch of caveats, that maybe there is something to learn there, you've found the right person.
If you're learning C, a lot of the old Bell Labs stuff is really worth looking at (and a lot isn't). I admire the work of Jon Bentley, Brian Kernighan, and Rob Pike, among many others. You can download and read the source of the original awk, or Pike's interpreter for Newsqueak.
Popularity does not correlate with suitability for learning. The GNU tools are very popular, but almost anyone who has seen both will tell you that you will learn more from the Bell Labs versions. And Linux is very popular, but people I trust who work in the field tell me that if you want to learn about operating systems, you should study BSD. I myself work in the field of compilers and can tell you that if you want to write a compiler in C, the model to emulate is the little-known lcc, not the wildly popular gcc.
Finally, I highly recommend the work of Richard Bird, Hans Boehm, Ralf Hinze, and Phong Vo (two Haskell programmers and two C/C++ programmers).
What I've found useful over the years, is to validate your code, go through coding conventions and best practices for various languages. Open Standards are the inevitable part of Open Source Software. In order to maintain a successful OSS project, it has to have some common ground in the community, so for instance:
if doing some (X)HTML and CSS, always do it by the W3C standards. Passing validation will in itself improve your skills greatly. Use tableless markup (see Benefits of tableless design);
if doing some PHP, go through PEAR coding standards which is the de facto standard for all OSS PHP projects;
if doing some Flash Platform coding in Flex/ActionScript, see Flex SDK coding conventions and best practices;
if doing some Java, see Code Conventions for the Java™ Programming Language.
Lastly, but not less importantly, research Object oriented programming and various architectures used for software development, e.g. the MVC pattern.
... analyzing others people code is a must in order to have a career in this field.
I wouldn't say that is correct. Certainly it is not a must. Reading other people's code doesn't usually explain why they chose to solve a problem a certain way, and what alternatives they considered and then dismissed. Besides, it is not uncommon to find open source code that is badly designed and/or badly implemented.
The problem is that ... but sometimes i can't solve the problems by my own.
Ah. Well the solution to that is to practice, practice, practice, and not be afraid to make mistakes. Be self-critical, but don't let this stop you from "having a go". The more you do your own problem solving, the easier it will become.
Ask, ask, ask, ask if you come across a particular problem or solution that you don't understand. Make a good-faith effort to solve the problem or to understand a solution, share your thought process, and ask. SO is an excellent place for that, which you undoubtedly have already discovered. Good luck!
As other said, ask to the mailing list of the project, anyway some of open source developers are not willing to help (unfortunately) for this sort of things.
In this situation I search answers by myself: pick up a terminal and use grep.
Guess naming of classes/functions that involves your problem you will find the way toward the module where the interesting bits are written.

Where to find programming projects that help science? [closed]

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I would like to work on a programming project in my spare time and would like to know
if there is a project where I can help the science community in some way?
Sure, plenty! I see I'm not the first to think of numerical computation libraries like Numpy/Scipy - the code in that is actually fairly mature but they could certainly use help documenting. There's also GNU Octave, which does much of the same things as Numpy but doesn't require Python. A slightly related area in which there's a lot of work to do is computer algebra systems (CAS), basically open source equivalents of Mathematica; for example Maxima, and more are listed at http://sage.math.washington.edu/home/wdj/sigsam/opensource_math.html. You could also help with visualization libraries, i.e. creation of 2D and 3D plots and figures. For Scipy the most commonly used plot generator is Matplotlib, for example. There are also loads of more specialized data visualization tools that I'm sure you can find with a few searches.
One area that I personally think needs a lot of work is creating GUIs for the programs mentioned in the previous paragraph; one major advantage that commercial programs like Matlab and Mathematica enjoy over their open source equivalents is easy-to-use graphical interfaces. Having a nice usable interface would be great for scientists who may not be skilled in command-line-fu, but open source projects have a long way to go if they're going to catch up.
Projects like scipy and numpy are largely contributed by the scientific community. I'm sure they would appreciate any help you thought you could provide.
I know BOINC is always looking for help
Edit: Here is their programming help page http://boinc.berkeley.edu/trac/wiki/DevProjects
The Bio* projects like BioPerl, BioPython, or BioRuby would certainly like some help, too.
http://sourceforge.net/search/?type_of_search=soft&words=science
In addition to searching open source projects online, you can try to contact your local university and ask if any of their researchers (students or faculty) need development help.
If you are still looking, feel free to contact me via my profile page - I know of a hardware product that needs software - it is used for research (chemistry and biology)
The nuclear ad particle physics communities make heavy use of ROOT, which is developed using an open source methodology. They accept suggestions and patches without much trouble. The main work is in C++, but there are binding and support for other languages as well.
I'm sure that other disciplines have their own domain specific tools. For instance, I know that there are open Computational Fluid Dynamics and Finite Element systems.
Have a look around. While domain knowledge would be helpful, most big tools are going to need help with routine stuff like RDBMS access, GUIs, documentation, and so on...
You can discover the current problems of Science by reading the abstracts of the academic journals. e.g. the Bioinformatics journal.
A few examples:
Find a faster/efficient methods to assemble a huge set of short DNA reads:
Find a way to build an efficient social scientific network
Find a way to compare thousand of human genomes
....
you could also propose your help on Nature Network:Collaboration or FriendFeed: The life scientists
There are many exicting opportunities in chemistry. There is a strong Open Source community, much of which is organized under the Blue Obelisk (http://www.blueobelisk.org). There have been major contributions in visualisation and algorithms which did not need previous chemical knowledge and the community is very welcoming to anyone who wishes to help.
For an example of the standard which has been achieved take a look at Jmol which visualizes molecules and other chemistry in 3D (http://www.jmol.org);
There is also real opportunity to do porting between platforms/languages. The commonest ones are Java, Python, C++ and we have been working in C#. You don't have to be an ace programmer either - contributions to data standards, data resources, tutorials, packaging, installers, testing, etc. are all highly valued.
Some of these projects are within the top 100-500 projects on Sourceforge.
Don't forget that if you find a project to be a bit over your head or you aren't able to really contribute, but you still like the idea of it, you can always donate!

What does it take to make a language successful? [closed]

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I have an interesting idea for a new programming language. It's based on a new programming paradigm that I've been working out in my head for some time. I finally got around to start working on a basic parser and interpreter for it a few weeks ago.
I want my new language to be successful and I want to eventually create a community around it when it's ready to release. The idea behind it is fairly innovative, so I don't expect it to gain a lot of ground in the business world, but it would thrill me more than anything else to see a handful of start ups use or open source projects use it.
So taking those aims into account, what can I do to help make my language successful? What do language projects do to become successful? What should I avoid at all costs? I'd love to hear opinions or stories about other languages -- successful or not -- so I can think about them as I continue to develop.
So far, the two biggest concerns on my mind are finding a market, access to existing libraries, having amazing tool support. What else might I add to this list?
The true answer is by having a beard.
http://blogs.microsoft.co.il/blogs/tamir/archive/2008/04/28/computer-languages-and-facial-hair-take-two.aspx
Although not specific to new programming languages, the book Producing Open Source Software by Karl Fogel (available to read online) may be contain some hints to the issue of making a community around your new programming language.
In terms of adoption of programming languages in general, it seems like the trend lately has been to have a rich library to make development times shorter.
As there isn't much detail on what your language is like, it's hard to determine whether adoption of the language is going to depend on the availability of a rich library. Perhaps your language will be able to fill a niche that has been overlooked by other languages and be able to gain users. Or perhaps it has a slick name that will draw people in -- there are many factors which can affect the adoption of a language.
Here are some factors that come to mind when thinking about recent successful languages:
Ability to leverage existing libraries in the new language.
Having an adapter to external libraries written in other languages.
Python allows access to code written in C through the Python/C API.
Targeting a platform which already has plenty of libraries available for use.
Groovy and Scala target the Java platform, therefore allowing the use of and interoperation between existing Java code.
Language design and syntax to allow increased productivity.
Many dynamically-typed languages have gained popularity, such as Ruby and Python to name a couple.
More concise and clear code can be written in languages such as Groovy, as opposed to verbose languages such as Java.
Offering features such as functions as first-class objects and closures which aren't offered in more "traditional" languages such as C and Java.
A community of dedicated users who also are willing to teach newcomers on the benefits of a language
The human factor is going to be big in wide-spread support for a language -- if people never start using your language, it won't gain more users.
Also, another suggestion that I could add is to make the development of your language open -- keep your users posted on developments in your language, and allow people to give you feedback. Better yet, let your users take part in the decision-making process, if you feel that is appropriate.
I believe that by offering ways to participate in the bringing up of a language, the more people will feel that they have a stake in the success of the new language, so the more likely it will gain more support.
Good luck!
Most languages that end up taking off rapidly do so by means of a killer app. For C it was Unix. Ruby had Rails. JavaScript is the only available programming system common to most browsers without third-party add-ons.
Another means of success is by fiat. This only works if you have significant clout. For example C#, as nice as a language as it might be, wouldn't be any where near as popular as it is now if Microsoft had not pushed it as hard as it does. Objective-C is the language of MacOS X simply because Apple says so.
The vast majority of languages, though, which lack a single killer app or a major corporate backer have gained success through long term investment of their respective creators. Perl and Python are prime examples. C++ has no single entity behind it, but it has evolved as the needs of developers have changed.
Don't worry about trying to make the language be successful; worry about using it to solve real problems and make real money.
You'll either make lots of money from using this language, or not. Once you have lots of money, others may care how you did it. Or not, either way you have lots of money.
If you don't make lots of money, nobody will want to know how you did it.
Edit based on comment: I define successful as people using it, and people use languages to solve problems, most for profit, thus successful == profitable.
In addition to making the language easy to use (which has several meanings), you should develop a comprehensive library that covers and also provides a good level of abstraction over (the following most important areas):
* Data structures and manipulation
* File I/O support
* XML processing
* Networking (plus web based technologies like HTTP/HTTPS)
* Database support
* Synchronous and asynchronous I/O
* Processes and threads
* Math
A well thought out framework that makes rapid development faster (and easier to maintain) would be a great addition. For this, you should know the currently popular frameworks well.
Keep in mind that it takes a lot of time. I think it took python about 10 years (someone please correct me if I'm wrong).
So even if your community still seems small after say, 5 years, that's not the end of the story.
"It's based on a new programming paradigm that I've been working out in my head for some time."
While laudable, odds are really good that someone has already done something with your "new" paradigm.
To make a language usable, it must build on prior art. Totally new is not a good path to success. My favorite example is Algol 68.
Algol 60 was wildly popular (back in the day, which is a while ago, admittedly).
The experts wanted to build on this success. They proposed some new paradigms, the effort split into factions. The purists put the new paradigms into Algol 68; it disappeared into obscurity. Some folks created a different version of Algol, called PL/I. It did not have any really new paradigms. It actually went somewhere and was used heavily. Another group created Pascal -- it didn't have much that was new -- it discarded things from Algol 60. It actually went somewhere ans was used heavily.
Your new paradigm must have a clear and concise summary so people can fit it into a context of where the language is usable, how it can be used, what the costs and benefits of using it are.
A "new programming paradigm" causes some people to say "why learn a completely new paradigm when the ones I have work so nicely?" You have to be very clear on how it helps to have a new paradigm.
The language and libraries must work, and work very, very well. A language that isn't rock-solid is worthless. In order to be rock-solid it must be very simple.
It has to have a tutorial that will help anyone get started with your language.
Good Framework for Common Tasks
Easy Installation/Deployment
Good Documentation
Debugger/IDE and other Tools
A popular flagship product that uses your language!
Good documentation, including a detailed reference manual as well as simple examples to get people started quickly.
Good library support so that people can actually write useful programs.
Most popular languages seem to be very strong in either or both or both of those.
Use Trojan Horse approach
C++ - The Forgotten Trojan Horse
An interesting article on why C++ can grab the heart of programmers successfully.

which were your achievements in programming in 2008? [closed]

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which were your achievements in programming in 2008?
what technologies surprise you or learn this year and what do you expect in programming terms in 2009
Edit:
Changed to Wiki
I wrote 2 VB.NET language features that will ship as part of VS 2010.
I designed a programing language called Liberty,
However, I've only implemented a small fraction of it. I stopped working on it so that I could concentrate on building a profitable software company. My original intent was to market the language (actually an IDE for it) as my first product, but the economics of programing languages being as they are, I decided to pick something else for my company's first product. I've been thinking about turning it into an open source project. If the statement "A programing language that feels like LISP, but looks like C#..." has any appeal to you, and you are interested in working on an open source .NET compiler, let me know.
I started my own software company
I've designed and implemented most of my company's first product "Transactor Code Agent", which should be shipping in Q1 2009. I've been billing it as a "Disaster Recovery Tool for Programmers".
It's a tool that provides automatic local version history for source code. You point it at the folders that contain your source, and then anytime you make a change to file it automatically creates a backup for you. It's meant to be a compliment to existing source control setups, by protecting all the "broken", "in-progress" work that you usually don't check into source control.
By the way, we are looking for beta-testers. If you are interested let me know.
After Scott's outing I would feel deep shame in confessing what I achieved in 2008.
I made one of my "flagship" applications better by removing features from it.
For the first time, I sold my work to a general audience, via the App Store. In so doing, I:
Reached over five times as many users as my most widely-used previous work (26000+ instead of 5000+)
Made more than three times as much money as my most lucrative previous work (a Google Summer of Code grant in 2005)
Learned two new environments (Objective-C/Cocoa Touch and Ruby/Rails) after sticking with Perl for many years
Disciplined myself enough to get the boring bits done
Learned what it meant to be responsible to thousands of people
But perhaps most importantly, I made beautiful things that I could be proud of.
In 2009 (or maybe late '08) I'll release a new product that I hope will push all of that even farther, and maybe even be a best-in-class solution for a problem everybody faces.
Helped push another release towards the door (not quite there yet)
Presented a paper on accelerating the Hough Transform at WorldComp
Averaged just shy of one blog post per week
Built up hope of catching John Skeet in reputation
Did a huge set of bizarro work with reflection and dynamic code generation
Gave up all hope of catching John Skeet in reputation
Managed three employees, more or less successfully
I decided I would learn a new language, nothing specific at the time, since then I have learned Python.
This coming year, I would like to learn another language, preferably something like c++ or maybe just maybe (I'm a *nix kinda' guy) Ill try a Microsoft stack with something like .net but we'll see what happens.
Improved interviewing skills. I am now better able to discern good and bad applicants through better questions, including small whiteboard coding sessions.
I am up to speed with Drupal, though lots still to learn. First time really working with a good framework.
2009, maybe i'll get around to doing some lisp funness
I opened myself to the world of Dynamic Languages and Functional Languages. I can read programs that dont resemble a C++ or C# kind of code with {} and ;. In the process developed better understanding to patterns like MVC.
I needed to learn PF early this December as our existing firewall solution was woefully underpowered for an industrial application, but we didn't have the dough for the "professional" solutions (i.e. ci$cso stuff).
So I ended up taking my existing OpenBSD box in the server stack and turn it into the firewall using PF. Since the system uses multiple servers and multiple IP's (some on domains), I needed a combination of NAT, RDR and the usual RULES.
It's certainly not as sexy as learning APL or LISP (or Ruby etc.) for fun, but it was necessary and urgent.
The new firewall is performing beautifully and I don't have to reset the horrid little firewall appliances twice a week anymore (which had to be done remotely which also was not fun). :-)
Cheers,
-Richard
Well, I've builded a big site (for some project) and learned java, now I want to learn C for coming year.
I released my first program into the wild world of the Internet.
I went outside my .NET bubble by creating the previously mentioned program in Objective-C.
I built a pretty cool string extractor utility and corresponding processing library to facilitate automatic localization of string resources in a native C++ application without refactoring the code to extract the strings from where they were used, with the added benefit of allowing cross-language string pooling of localized strings.
I also built a cool operator_cast<> function (with some help from the SO community) to help codify programming intent when using custom casting operators.
1- I made changes to a International Wine Contest Software that i previously wroted. it was changed because the a new sponsor have a different logic in the contest we were notified about the changes 3 days before, so a friend and I code like 2 days in a row,literally running from work to the contest in order to provide support. at the end everything was Flawless
2.- Released my first program for Sales and inventory for Video game retailer
3.- Start my Coding Blog
both in .Net of Course

Open source expert system [closed]

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does anyone know about a open source expert system? actually, I'm rather interested in calling its inferential engine from C#.
Both CLIPS and JESS are already mentioned in other answers, so I will supply this link to CLIPS versus JESS:
http://www.comp.lancs.ac.uk/~kristof/research/notes/clipsvsjess/
It was written June 4, 1999, and at that time the advantage was clearly with CLIPS.
If you don't want to read it all, here are the conclusions:
Chapter 3 The conclusions
Both CLIPS and JESS are products with a large support on the internet,
but CLIPS seems to have a broader audience, probably because it exists
longer. This difference in age results in the CLIPS package being more
stable and complete, while JESS users will still experience some minor
bugs. JESS is constantly updated and the author, Ernest Friedman-Hill,
has been very responsive to user/developer feedback and regularly puts
out new releases and bug fixes.
Nowadays, the choice between JESS and CLIPS depends on the
application. If it is web-based or should reside in applet-form, the
choice of JESS is a very logical one (which is even supported by the
authors of CLIPS). For the more classic applications, CLIPS will
probably be chosen because of its reputation of being more stable and
having more support.
The future of JESS depends highly on the evolution of the web, the
Java programming language and its own future stability. These three
conditions make that there is a great possibility that JESS will
become more popular and more frequently used. Especially the
object-oriented possibilities and the easy integration into Java code
makes JESS’ future very promising.
CLIPS, on the other hand, is more likely to implement the new and
sophisticated features first as they come out, since it still has the
advantage in time. CLIPS has also various extensions and variants(like
FuzzyCLIPS, AGENT CLIPS, DYNACLIPS, KnowExec, CAPE, PerlCLIPS, wxCLIPS
and EHSIS to name a few) that give it an advantage with respect to
support of methods like fuzzy logic and agents.
The multifunctional developing environment of CLIPS for operating
systems that support windows is also an advantage, while JESS has just
one window with two buttons (‘clear window’ and ‘quit’), without a
menu. Figures 1 and 2 depict both environments.
To summarize, CLIPS is still more complete and stable than JESS, but
this might change in the future, since the JESS package is being
improved constantly. Besides that, JESS has also the property of using
Java, which in the long run might prove to be a big advantage over
CLIPS.
These links may also be of interest:
http://en.wikipedia.org/wiki/CLIPS
Commercial & Freeware Expert System Shells
http://www.kbsc.com/rulebase.html
Are there open source expert systems with reasoning capabilities?
I went through the same process, about a year ago, trying to find a good .Net system for this. I recall finding a few decent engines, but they were all too general, and required too many assumptions.
In the end I found that writing my own system was pretty easy to do, and it did exactly what I wanted it to, without any extra bull to make it work with some abstract generalized engine.
It might help to know what your intended use is.
Take a look at CLIPS -- it is coded in C.
There's more info on CLIPS at Wikipedia.
If you'd consider a rule-processing engine, JBoss Rules (also known as Drools) is the best that I know of. Open Source and free. It's written in Java, but designed for integration. You can incorporate objects in the rules and rule-base applications in your components. You can even build or modify rule-bases on the fly.
AI::ExpertSystem::Advanced or AI::ExpertSystem::Simple is a Perl solution.
You can try JESS, but it is Java-based. Amzilogic also provide a good platform.