The evolution of complete software systems

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@PhdThesis{Withall:thesis,
  author =       "Mark S. Withall",
  title =        "The evolution of complete software systems",
  school =       "Department of Computer Science, Loughborough
                 University",
  year =         "2003",
  address =      "UK",
  month =        "13 " # jun,
  keywords =     "genetic algorithms, genetic programming,
                 Representation,Formal specification, Graphical user
                 interfaces, Complete software systems",
  URL =          "http://hdl.handle.net/2134/3594",
  URL =          "https://dspace.lboro.ac.uk/dspace-jspui/bitstream/2134/3594/1/MSWthesis.pdf",
  URL =          "http://ethos.bl.uk/OrderDetails.do?did=41&uin=uk.bl.ethos.515618",
  size =         "178 pages",
  abstract =     "This thesis tackles a series of problems related to
                 the evolution of complete software systems both in
                 terms of the underlying Genetic Programming system and
                 the application of that system.

                 A new representation is presented that addresses some
                 of the issues with other Genetic Program
                 representations while keeping their advantages. This
                 combines the easy reproduction of the linear
                 representation with the inheritable characteristics of
                 the tree representation by using fixed-length blocks of
                 genes representing single program statements. This
                 means that each block of genes will always map to the
                 same statement in the parent and child unless it is
                 mutated, irrespective of changes to the surrounding
                 blocks. This method is compared to the variable length
                 gene blocks used by other representations with a clear
                 improvement in the similarity between parent and child.
                 Traditionally, fitness functions have either been
                 created as a selection of sample inputs with known
                 outputs or as hand-crafted evaluation functions. A new
                 method of creating fitness evaluation functions is
                 introduced that takes the formal specification of the
                 desired function as its basis. This approach ensures
                 that the fitness function is complete and concise. The
                 fitness functions created from formal specifications
                 are compared to simple input/output pairs and the
                 results show that the functions created from formal
                 specifications perform significantly better. A set of
                 list evaluation and manipulation functions was evolved
                 as an application of the new Genetic Program
                 components. These functions have the common feature
                 that they all need to be 100percent correct to be
                 useful. Traditional Genetic Programming problems have
                 mainly been optimisation or approximation problems. The
                 list results are good but do highlight the problem of
                 scalability in that more complex functions lead to a
                 dramatic increase in the required evolution
                 time.

                 Finally, the evolution of graphical user interfaces is
                 addressed. The representation for the user interfaces
                 is based on the new representation for programs. In
                 this case each gene block represents a component of the
                 user interface. The fitness of the interface is
                 determined by comparing it to a series of 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 of complete software systems is now a
                 realistic goal.",
  notes =        "725.86 kB

                 Chapter 4 Evolving Some Interesting Functions 4.2
                 Sumlist 4.3 Avelist 4.4 Listmax 4.5 Listmin 4.6 Reverse
                 4.7 Sort

                 Chapter 5 Evolving the User Interface 5.5 Example
                 Problems 5.5.1 A Text Editor 5.5.2 A Personal Details
                 Web Form 5.5.3 A Front-end for the List
                 Functions

                 uk.bl.ethos.515618",
}

Genetic Programming entries for Mark S Withall

Citations