Binary trees are seen and used frequently in computing science and computing. They are a good abstraction for many naturally occurring relationships (most of our mathematics is based on binary operations, for instance) and have O(log n) complexity (ie if you went from searching a tree of 1000 elements to a tree of 100,000 elements then the search should not take 100 times longer but about 10.)
Of course that log n goodness requires the tree to be “balanced” ie for any given node there should be roughly equal numbers to the left and the right. One way of doing this is through a “red black tree” – here nodes in the tree are assigned a colour: the root is always black. The rule is that any traversal from the root to the leaves should always go through an equal number of black nodes and to ensure this is possible red nodes may be inserted in the tree, but no red node may have another red node as an immediate descendant. (A full explanation is in Introduction to Algorithms though one can also work off various explanations on the internet, though they tend to be less than complete.)
The Linux kernel natively implements a red black tree (in C) and the first bit of work I started on my MSc project was to write my own, userland, implementation so I could see processes in the same way the kernel did.
As I had got a less than glorious mark (still a pass, so that’s what counts) in the C++ exam last year I also decided that I would write this in C++ using templates. A few days after I started I discovered that actually the writers of the STL had got there before me, but as this was an academic exercise I ploughed on with my own implementation.
Essentially this is what I did on my two week summer holiday in Scotland last year! When I was there I also started (though completed when I got home) a couple of helper applications to position the tree according to Reingold and Tilford’s algorithm (which I had to translate from PASCAL) for “better drawing of trees” and a Qt application to display it all.
In fact I had a nagging problem with the Reingold-Tilford algorithm which I finally got around to fixing last night.
(Interestingly the code also allows you to use the Turing-complete capabilities of LaTeX by specifying a TeX output that uses LaTeX’s own positioning algorithm – something I picked up from The LATEX Graphics Companion – that is what the example shown above uses, though unfortunately for even moderately loaded systems the LaTeX processor objects to the width of the output).
Fancy trying it? I could do with someone giving it a bash on a BSD system – not needed for my course but interesting none the less.
The code is all at GitHub – http://github.com/mcmenaminadrian: memball gives the basic GraphML or TeX or plaintext output, treedraw will convert the GraphML to an SVG or serialiszed stream using Reingold and Tilford’s algorithm and treeqt will use Qt to display
the tree using the serialized class. You may have to download various libraries to get it to work (certainly the libproc-dev package on Ubuntu/Debian) – I couldn’t get memball to work on a Windows machine using Cygwin but maybe even that is fixable.
There is a script in the treeqt repo to make it easier: download the sources form all three repos, build them and then run:
./setup | ./treeqt --r 1
(Update: Treeqt does not display an SVG – so I have updated the text to reflect that)
- Brushing Up on Computer Science Part 3, Data Structures (victusspiritus.com)
- Interesting but lesser known data structures (stackoverflow.com)
- Hierarchical edge bundles (seeingcomplexity.wordpress.com)
- Skip Lists are Fascinating (igoro.com)
- Nedtries: an ordered container faster than hash tables and red-black trees (nedprod.com)