Genetic Programming + Proof Search = Automatic Improvement

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{PolyfinicJAR,

• author = "Zoltan A. Kocsis and Jerry Swan",
• title = "Genetic Programming + Proof Search = Automatic Improvement",
• journal = "Journal of Automated Reasoning",
• year = "2018",
• volume = "60",
• number = "2",
• pages = "157--176",
• month = feb,
• keywords = "genetic algorithms, genetic programming, Genetic Improvement, GGGP, Program Synthesis, Software Maintenance, SBSE, Search Based Software Engineering",
• ISSN = "1573-0670",
• URL = "http://eprints.whiterose.ac.uk/117917/",
• URL = "http://eprints.whiterose.ac.uk/117917/1/art_10.1007_s10817_017_9409_5.pdf",
• DOI = "doi:10.1007/s10817-017-9409-5",
• size = "22 pages",
• abstract = "Search Based Software Engineering techniques are emerging as important tools for software maintenance. Foremost among these is Genetic Improvement, which has historically applied the stochastic techniques of Genetic Programming to optimize pre-existing program code. Previous work in this area has not generally preserved program semantics and this article describes an alternative to the traditional mutation operators used, employing deterministic proof search in the sequent calculus to yield semantics-preserving transformations on algebraic data types. Two case studies are described, both of which are applicable to the recently-introduced grow and graft technique of Genetic Improvement: the first extends the expressiveness of the grafting phase and the second transforms the representation of a list data type to yield an asymptotic efficiency improvement.",
• notes = "Scala source code Curry-Howard isomorphism POLYFUNIC PMID: 30069068",

}

Genetic Programming entries for Zoltan Kocsis Jerry Swan

Citations