- author = "William B. Langdon and Justyna Petke",
- title = "Evolving Better Software Parameters",
- booktitle = "SSBSE 2018 Hot off the Press Track",
- year = "2018",
- editor = "Thelma Elita Colanzi and Phil McMinn",
- volume = "11036",
- series = "LNCS",
- pages = "363--369",
- address = "Montpellier, France",
- month = "8-9 " # sep,
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, genetic improvement, software engineering, SBSE, GGGP, software maintenance of empirical constants, data transplantation, glibc, sqrt, cbrt",
- isbn13 = "978-3-319-99241-9",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/Langdon_2018_SSBSE.pdf",
-
DOI = "
doi:10.1007/978-3-319-99241-9_22",
- size = "7 pages",
- abstract = "Genetic improvement might be widely used to adapt existing numerical values within programs. Applying GI to embedded parameters in computer code can create new functionality. For example, CMA-ES can evolve 1024 real numbers in a GNU C library square root to implement a cube root routine for C.",
-
notes = "See also \cite{Langdon:TELO}
code: http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/gp-code/gi_cbrt.tar.gz https://github.com/oliver-krauss/Replication_GI_Division_Free_Division see also \cite{replication_package}
slides: http://www.cs.ucl.ac.uk/staff/W.Langdon/ssbse2018/Langdon_2018_SSBSE_slides.pdf",
