- author = "William B. Langdon and Mark Harman",
- title = "Optimising Existing Software with Genetic Programming",
- journal = "IEEE Transactions on Evolutionary Computation",
- year = "2015",
- volume = "19",
- month = feb,
- number = "1",
- pages = "118--135",
- keywords = "genetic algorithms, genetic programming, genetic improvement, Software, Search methods, genetic algorithms, SBSE, automatic software re-engineering, Bowtie2GP, multiple objective exploration",
- ISSN = "1089-778X",
-
URL = "
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6733370",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/Langdon_2013_ieeeTEC.pdf",
-
URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/bowtie2_supplementary.pdf",
-
video_url = "http://youtu.be/Ut0qERy9yZQ",
-
code_url = "http://crest.cs.ucl.ac.uk/bowtie2gp/",
-
DOI = "
doi:10.1109/TEVC.2013.2281544",
- size = "18 pages",
- abstract = "We show genetic improvement of programs (GIP) can scale by evolving increased performance in a widely-used and highly complex 50000 line system. GISMOE found code that is 70 times faster (on average) and yet is at least as good functionally. Indeed it even gives a small semantic gain.",
-
notes = "Follow up to \cite{Langdon:RN1209}
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/gp-code/bowtie2gp/gp_sources
FTP kit Copy in
http://crest.cs.ucl.ac.uk/bowtie2gp/
YouTube Video http://youtu.be/Ut0qERy9yZQ
Slides etc from 15 October 2013 presentation http://crest.cs.ucl.ac.uk/cow/28/
Also known as \cite{6733370}",
