Genetic Improvement in Code Interpreters and Compilers

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Oliver Krauss",
  title =        "Genetic Improvement in Code Interpreters and
  booktitle =    "Proceedings Companion of the 2017 ACM SIGPLAN
                 International Conference on Systems, Programming,
                 Languages, and Applications: Software for Humanity",
  year =         "2017",
  series =       "SPLASH Companion 2017",
  pages =        "7--9",
  address =      "Vancouver, BC, Canada",
  publisher =    "ACM",
  keywords =     "genetic algorithms, genetic programming, Genetic
                 Improvement, Code Optimization, Compilation,
  isbn13 =       "978-1-4503-5514-8",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1145/3135932.3135934",
  acmid =        "3135934",
  size =         "3 pages",
  abstract =     "pplicability of GI in an offline phase directly at the
                 interpreter or compiler level. The primary goal is to
                 reformulate existing source code in such a way that
                 existing optimizations can be applied in order to
                 increase performance even further and requiring even
                 less domain knowledge from the developer about a
                 programming language and/or compiler. From these
                 reformulations, patterns can be identified that allow
                 code restructuring without the overhead GI poses.",
  notes =        "p8 'apply GI in Truffle and Graal' Heuristic Lab.
                 Abstract syntax tree AST rewritten by GI. p9
                 'automatically create a regression test suite' using
                 'Randoop or EvoSuite'. monitor program internal

                 Also known as \cite{Krauss:2017:GIC:3135932.3135934}",

Genetic Programming entries for Oliver Krauss