- author = "Zsolt Nemeth and Penn {Faulkner Rainford} and Barry Porter",
- title = "Ecosystem Curation in Genetic Improvement for Emergent Software Systems",
- booktitle = "13th International Workshop on Genetic Improvement @ICSE 2024",
- year = "2024",
- editor = "Gabin An and Aymeric Blot and Vesna Nowack and Oliver Krauss and and and Justyna Petke",
- address = "Lisbon",
- month = "16 " # apr,
- publisher = "ACM",
- note = "Best position paper",
- keywords = "genetic algorithms, genetic programming, Genetic Improvement, demes, subpopulations, inhomogeneous populations, hierarchical populations, speciation, phenotype diversity, co-evolution, hash function",
- isbn13 = "979-8-4007-0573-1/24/04",
-
URL = "
http://gpbib.cs.ucl.ac.uk/gi2024/GI_ICSE2024_Nemeth.pdf",
-
DOI = "
doi:10.1145/3643692.3648260",
-
slides_url = "http://gpbib.cs.ucl.ac.uk/gi2024/gi_2024_slides/gi_icse2024_nemeth.pdf",
- size = "2 pages",
- abstract = "Emergent software systems are composed, and continuously recomposed at runtime, from a large pool of small potential building blocks with the aim of responding to changes in the deployment environment [REX]. The approach assumes that each building block has a set of available variations in the selection pool, such that the most appropriate collection of variants can be composed according to the current conditions, with some objective function in mind. Populating such a pool of implementation variation, however, is not a trivial task, and existing work has examined the use of Genetic Improvement (GI) to drive this process \cite{rainford:2022:GECCO}",
-
notes = "store high-utility genetic material
GI @ ICSE 2024, part of \cite{an:2024:GI}",
