The evolution of complete software systems

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.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Comparing content-filter techniques for stopping spam

There are many new theoretical techniques for detecting spam e-mail based upon the message contents. Although Bayesian methods are the most wellknown, there are other approaches for classifying information. This paper establishes some criteria for measuring spam filter effectiveness and compares the Boosting and Support Vector Machine approaches with some well-known existing filter software. It also examines ways of transforming e-mail messages into a form which is more readily processable by such algorithms

An improved representation for evolving programs

A representation has been developed that addresses some of the issues with other Genetic Program representations while maintaining their advantages. This combines the easy reproduction of the linear representation with the inherita- ble 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. In addition, 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 100% correct to be useful. Traditional Genetic Programming problems have mainly been optimization 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

Evolving readable Perl

A program is informally deemed readable, for the purpose of this experiment, if it is easy for a person to follow the steps that the program takes to solve the problem. In this experiment, readability is achieved by constraining the available syntax for generating solutions. The Genetic Programming (GP) system created uses the target language Perl because it is an interpreted, untyped, robust procedural language which has good error handling and recovery

Evolving the user interface

A method is presented for evolving Graphical User Interfaces using Genetic Algorithms. The fitness evaluation is based on a series of constraints, which must be met by the user interface. Examples are used to demonstrate the use of positional, style and functionality constraints and the final example shows the evolution of a complete (although simple) software application

Evolving Perl

A list of requirements for a genetic programming representation is put forward and a representation separating the genotype and phenotype with a linear genome is presented. The target language for the genetic program is Perl. The mapping process, between the genotype and phenotype, converts blocks of four genes into program statements. This process is context-free and therefore provides inheritable characteristics. The representation is tested by evolving a selection of list evaluation and manipulation functions which are all evolved from the same language subset, with good results

Packet transmission optimisation using Genetic Algorithms

A Genetic Algorithm (ga) is used to optimise the parameters for a sequence of packets sent over the Internet. Only the parameters that a client machine can change are used and the fitness is based on the delay time returned by the Traceroute program. The ga performance is compared to a fixed packet size with no priority used to assess the status of the network. The ga generally performed to the same level as the control settings but in some cases significant improvements were made

Honey Plotter and the Web of Terror

Honeypots are a useful tool for discovering the distribution of malicious traffic on the Internet and how that traffic evolves over time. In addition, they allow an insight into new attacks appearing. One major problem is analysing the large amounts of data generated by such honeypots and correlating between multiple honeypots. Honey Plotter is a web-based query and visualisation tool to allow investigation into data gathered by a distributed honeypot network. It is built on top of a relational database, which allows great flexibility in the questions that can be asked and has automatic generation of visualisations based on the results of queries. The main focus is on aggregate statistics but individual attacks can also be analysed. Statistical comparison of distributions is also provided to assist with detecting anomalies in the data; helping separate out common malicious traffic from new threats and trends. Two short case studies are presented to give an example of the types of analysis that can be performed