Genetically Improved Software

title = "Genetically Improved Software",

booktitle = "Handbook of Genetic Programming Applications",

publisher = "Springer",

year = "2015",

editor = "Amir H. Gandomi and Amir H. Alavi and Conor Ryan",

chapter = "8",

pages = "181--220",

keywords = "genetic algorithms, genetic programming, mutation, genetic improvement GI, search based software engineering SBSE, software optimisation, gismoe, GPGPU, nVidia, GPU, Tesla K20c, GeForce gzip, bioinformatics, SAT, miniSAT, SPL, evolutionary programming, software engineering, Image analysis and signal processing, Artificial Intelligence, Automatic Programming",

isbn13 = "978-3-319-20882-4",

URL = "

http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/langdon_2015_hbgpa.pdf",

DOI = "

doi:10.1007/978-3-319-20883-1_8",

size = "40 pages",

abstract = "Genetic programming (GP) can dramatically increase computer programs' performance. It can automatically port or refactor legacy code written by domain experts and specialist software engineers. After reviewing SBSE research on evolving software we describe an open source parallel StereoCamera image processing application in which GI optimisation gave a seven fold speedup on nVidia Tesla GPU hardware not even imagined when the original state-of-the-art CUDA GPGPU C++ code was written.",