- author = "William B. Langdon",
- title = "The Genetic Improvement Fitness Landscape",
- institution = "University College, London",
- year = "2016",
- number = "RN/16/04",
- address = "London, UK",
- month = "10 " # jun,
- keywords = "genetic algorithms, genetic programming, genetic improvement, SBSE, theory, software engineering, search, heuristic methods",
-
URL = "
http://www.cs.ucl.ac.uk/fileadmin/UCL-CS/research/Research_Notes/rn1604.pdf",
-
data_url = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ppsn2016/triangle/",
- size = "5 pages",
- abstract = "Trying all simple changes (first order mutations) to executed source code shows software engineering artefacts are more robust than is often assumed. Of those that compile, up to 89percent run without error. Indeed a few non equivalent mutants are improvements.",
-
notes = "GISMO notme benchmark
http://www.cs.ucl.ac.uk/staff/W.Langdon/gggp/notme
See also \cite{langdon:2016:PPSNlandscape}",
