- author = "Oliver Krauss",
- title = "Amaru - A Framework for combining Genetic Improvement with Pattern Mining",
- booktitle = "GI @ GECCO 2022",
- year = "2022",
- editor = "Bobby R. Bruce and Vesna Nowack and Aymeric Blot and Emily Winter and W. B. Langdon and Justyna Petke",
- pages = "1930--1937",
- address = "Boston, USA",
- publisher_address = "New York, NY, USA",
- month = "9 " # jul,
- organisation = "SIGEVO",
- publisher = "Association for Computing Machinery",
- keywords = "genetic algorithms, genetic programming, genetic improvement, Compiler, Interpreter, Framework, Truffle, TPI, TPD, Graal VM, Java HotSpot VM, JVM, Neo4J, HeuristicLab, KGGI, syntax graph, Fibonacci, IGOR",
- isbn13 = "978-1-4503-9268-6/22/07",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/gecco2022/gi2022/papers/Krauss_2022_GI.pdf",
-
DOI = "
doi:10.1145/3520304.3534016",
-
slides_url = "http://geneticimprovementofsoftware.com/slides/gi2022gecco/krauss-framework-for-combining-gi-gecco-22.pdf",
-
code_url = "
https://oliver-krauss.github.io/amaru/",
-
video_url = "https://www.youtube.com/watch?v=3Ok1JzdAmFs&list=PLI8fiFpB7BoIHgl5CsdtjfWvHlE5N6pje&index=2",
- size = "8 pages",
- abstract = "We present Amaru, a framework for Genetic Improvement using Abstract Syntax Trees directly at the interpreter and compiler level. Amaru also enables the mining of frequent, discriminative patterns from Genetic Improvement populations. These patterns in turn can be used to improve the crossover and mutation operators to increase population diversity, reduce the number of individuals failing at run-time and increasing the amount of successful individuals.",
-
notes = "http://geneticimprovementofsoftware.com/events/gecco2022
Using system to generate secondary mutation (sub-AST) to the AST to compensate for primary mutation means likely to compile and may run ok.
knowledge of source code language can be used to 'prevent code bloat'. Guiding search based on guess of likely runtime branching.
GECCO-2022 A Recombination of the 31st International Conference on Genetic Algorithms (ICGA) and the 27th Annual Genetic Programming Conference (GP)",
