Internal Members

	Name	Ms. Corne de Ridder
	Subject	Approximate tandem repeat detection in DNA using Finite Automata
	Degree Obtained	BSc Honours (Computer Science), UNISA; BA (Philosophy, Psychology), University of Pretoria
	Current Degree	MSc in Computer Science, University of Pretoria
	email	Driddc@unisa ac za

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In terms of my masters I am applying finite automata technology on the field of bioinformatics. I am in particular proposing an algorithm that will contribute to the detection of microsatellites on genetic sequences. My other research interests include computer ethics and issues pertaining to the merger that the School of Computing at UNISA (University of South Africa) are confronted with.

	Name	Dr. Ernest Ketcha Ngassam
	Subject	Finite State Automata implementation
	Degree Obtained	BSc (Maths and Computer Science), University of Yaounde, Cameroon; BSc (Hons) in Computer Science, University of Pretoria; MSc in Computer Science, University of Pretoria; PhD in Computer Science, University of Pretoria
	Current Degree
	email	eketcha@cs up ac za

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My research interests include algorithmics, programming, performance, benchmarking, generative programming and software construction. I am currently working on taxonomies of finite automata implementations. My work entails exploring various strategies for implementing finite automata as acceptors with the aim at providing very efficient algorithms for fast string recognition. The algorithms are explored using a formal characterization of acceptors that yield derivations of several algorithms that may outperform existing ones. The ultimate goal of my research is four-folded: Provide automata implementers with efficient algorithms for fast string recognition with applications to well known problems such as: network intrusion detection systems, DNA analyzers, tandem repeat finders, natural and computer virus scanning, virtual circuit simulation, etc. Provide hardware designers with a comprehensive performance analyzer of finite automata related problems that may result in improving the structure of hardware components such as cache memory. Explore the possibilities to implement finite automata directly on hardware for performance enhancement. Explore the design of a unified framework for the dynamic implementation of finite automata.

	Name	Mr. David Fick
	Subject	The Suitability of .NET Reflection in Developing DSL's
	Degree Obtained	BSc Hons
	Current Degree	MSc in Computer Science, University of Pretoria
	email	dfick@grintek com

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My main areas of interests are compilers, graphics and artificial intelligence, and perhaps a means to tie together all three. I am currently pursuing a Master's degree under the guidance of Prof Watson and Prof Kourie regarding Domain Specific Language (DSL) compilers. This entails much experimentation with regular expressions, parsing regular expressions and different code generation techniques. I am mainly interested in how code can be generated for a DSL under the .NET architecture. Since the .NET architecture sports a generic runtime engine suitable for many different anguage disciplines, I am also experimenting with the idea of using the .NET architecture as the basis for aspect weaving, which should hopefully solve many of those "inconsistency" problems associated with large software engineering projects.

	Name	Dr.Ir. Loek Cleophas
	Subject	Taxonomies and toolkits of tree algorithms
	Degree Obtained	PhD in Computer Science, Technische Universiteit Eindhoven; MSc in Computer Science, Technische Universiteit Eindhoven
	Current Degree
	email	l g w a cleophas@tue nl

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My interests are various, including text & tree processing, finite (tree) automata, computational biology, computational linguistics, and software construction/architecture (including components, design patterns etc.). My PhD research focused on the application of the TABASCO method to tree automata and tree algorithms. This resulted in taxonomies for tree acceptance and pattern matching algorithms, and a toolkit of such algorithms. For my MSc thesis, I applied this method to (string) pattern matching (PM), i.e. extending a taxonomy of PM algorithms. In addition, I worked on an extension to the SPARE Parts pattern matching toolkit, called SPARE Time.