- author = "Oliver Krauss",
- title = "Genetic Improvement in Code Interpreters and Compilers",
- 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, Non-Functional",
- isbn13 = "978-1-4503-5514-8",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/SPLASH_SRC_Krauss_Oliver.pdf",
-
URL = "
https://2017.splashcon.org/event/splash-2017-doctoral-symposium-genetic-improvement-in-code-interpreters-and-compilers",
-
DOI = "
doi:10.1145/3135932.3135934",
- acmid = "3135934",
- size = "3 pages",
- abstract = "applicability 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
memory.
Also known as \cite{Krauss:2017:GIC:3135932.3135934}",
