Experiments in Automatic Programming for General Purposes

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{ReformatCM03,

• author = "Marek Reformat and Xinwei Chai and James Miller",
• title = "Experiments in Automatic Programming for General Purposes",
• booktitle = "Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI '03)",
• publisher = "IEEE Computer Society",
• year = "2003",
• pages = "366--373",
• month = nov,
• keywords = "genetic algorithms, genetic programming, automatic programming, fault tolerant computing, genetic algorithms, software prototyping, software reusability algorithm, automatic cone generation, automatic production, automatic programming, clone crossover, clone generation, clone mutation, clone selection, evolutionary-based genetic programming, fault tolerance, genetic programming, problem solving, software clone, software development, software engineering, software fault tolerance",
• DOI = "doi:10.1109/TAI.2003.1250213",
• abstract = "Although the generation and application of software clones is relatively unexplored, it is believed that this is a fundamental technology that can have many different applications within a software engineering environment. For example, software clones could be used in software fault tolerance. Clearly, for these clones to be usable, their production needs to be automated. An interesting approach to this automatic production or generation problem is the application of evolutionary-based genetic programming (GP). Using the paradigms of best fit, selection, crossover and mutation a number of clones, satisfying specific requirements, can be automatically generated. In general, GP is a flexible and powerful algorithm suitable for solving variety of different problems. The paper presents the results of studies that have been conducted in order to answer questions related to feasibility of using GP for clone generation: what features of GP are important? What works and what does not? How GP can be {"}tuned{"} for the problem? The results have been used to draw a set of suggestions and conclusions that indicate possible usability of GP-based approach to automatic generation of clones.",
• bibsource = "http://crestweb.cs.ucl.ac.uk/resources/sbse_repository/repository.html",
• notes = "Also known as \cite{1250213}",

}

Genetic Programming entries for Marek Reformat Xinwei Chai James Miller

Citations