New Adventures in Software by Dan Dyer

While some of us can just about muddle through a Sudoku, others are aiming higher. The BBC has the story of how a team from the University of Alberta has solved Checkers (or “Draughts” as we like to call it in this part of the world). The Chinook program was already well capable of beating the best human players, now it’s not worth even trying since it can’t be beaten. Earlier incarnations of Chinook made use of evolutionary approaches. The latest release is the result of a phenomenal amount of CPU time dedicated to analysing every possible game position and determining the best move for each. A solution for Chess is still some way off.

Everybody loves Sudoku (probably), and evolutionary computation is kind of neat, so what could possibly be better than an animated evolutionary Sudoku solver?

The applet’s animation gives a good feel for how the randomly directed search eventually converges on the right solution through the power of cumulative selection. Have a play with the population size setting to trade-off performance with reliability (harder puzzles will typically require a larger population).

I’ve got lots of ideas for improvements to the Watchmaker Framework for Evolutionary Computation, but before I could get started, I first had to finish off the stuff I had been playing with. So that’s what I’ve been up to this evening and the result is version 0.4.1.

• Changelog
• API Documentation

I discovered the Open Source project directory Ohloh yesterday (thanks to Andres Almiray’s post that I noticed on JavaBlogs). Oddly the name Ohloh is instantly forgettable and I’m having to look up the URL each time I go there.

By querying CVS and Subversion repositories, Ohloh generates information about the state of a project and ties individual contributions to developer profiles. It also allows individuals to list which Open Source projects they are users of. The site uses Google Maps to show how both contributors and users are distributed geographically.

I added my Watchmaker evolutionary computation project (the Ohloh entry is here). Unfortunately java.net‘s strategy of hosting web content in the Subversion repository does skew the statistics somewhat (my contributions appear to be mostly HTML content, but this is mainly generated Javadoc output).

Of the information presented, most pleasing for me is the nice green tick the project gets for being well commented:

Across all Java projects on Ohloh, 35% of all source code lines are comments. For Watchmaker Evolution Framework, this figure is 45%.

This high number of comments puts Watchmaker Evolution Framework among the highest one-third of all Java projects on Ohloh.

A high number of comments might indicate that the code is well-documented and organized, and could be a sign of a helpful and disciplined development team.

That’s a good reference for my CV: “Dan is a helpful and disciplined development team.” 🙂

JiBX is a library for XML data-binding. I’ve used it on a few projects over the last year or so. I used to use Castor XML. Castor had its quirks, but it worked. I decided to explore JiBX as an alternative when I saw the eye-opening BindMark performance benchmarks. JiBX’s elegant mapping mechanism made the conversion of the project I was working on pretty straightforward (without any of the awkward corner cases I came across with Castor). One quick performance test was enough to confirm that I wouldn’t ever be going back to Castor. The conversion to JiBX made the XML <-> POJO translations nine times faster.

The simpler mapping and astonishing performance boost were not the only plus-points. JiBX achieves its performance by using post-compilation bytecode manipulation rather than the reflection approach adopted by Castor and other similarly invasive XML data-binding solutions. This has the advantage that it places fewer demands on the way that you write your mapped classes. There is no need for getters, setters and no-arg constructors just to satisfy the tools. Most of the time you can write the class without considering mapping issues and then map it without modifications.

Denis Sosnoski shows what can be achieved by a single developer project. The code is clean, the documentation is good and the end result is a piece of software that I wouldn’t hesistate to recommend.