Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.515618
Title: The evolution of complete software systems
Author: Withall, Mark S.
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2003
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Abstract:
This thesis tackles a series of problems related to the evolution of completesoftware systems both in terms of the underlying Genetic Programmingsystem and the application of that system. A new representation is presented that addresses some of the issues withother Genetic Program representations while keeping their advantages. Thiscombines the easy reproduction of the linear representation with the inheritablecharacteristics of the tree representation by using fixed-length blocks ofgenes representing single program statements. This means that each block ofgenes will always map to the same statement in the parent and child unless itis mutated, irrespective of changes to the surrounding blocks. This methodis compared to the variable length gene blocks used by other representationswith a clear improvement in the similarity between parent and child. Traditionally, fitness functions have either been created as a selection ofsample inputs with known outputs or as hand-crafted evaluation functions. Anew method of creating fitness evaluation functions is introduced that takesthe formal specification of the desired function as its basis. This approachensures that the fitness function is complete and concise. The fitness functionscreated from formal specifications are compared to simple input/outputpairs and the results show that the functions created from formal specificationsperform significantly better. A set of list evaluation and manipulation functions was evolved as anapplication of the new Genetic Program components. These functions havethe common feature that they all need to be 100% correct to be useful. Traditional Genetic Programming problems have mainly been optimizationor approximation problems. The list results are good but do highlight theproblem of scalability in that more complex functions lead to a dramaticincrease in the required evolution time. Finally, the evolution of graphical user interfaces is addressed. The representationfor the user interfaces is based on the new representation forprograms. In this case each gene block represents a component of the userinterface. The fitness of the interface is determined by comparing it to a seriesof constraints, which specify the layout, style and functionality requirements. A selection of web-based and desktop-based user interfaces were evolved. With these new approaches to Genetic Programming, the evolution ofcomplete software systems is now a realistic goal.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.515618  DOI: Not available
Keywords: Genetic algorithms ; Genetic Programming ; Representation ; Formal specification ; Graphical user interfaces ; Complete software systems
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