- author = "Jerry Swan and Michael G. Epitropakis and John R. Woodward",
- title = "{Gen-O-Fix:} An embeddable framework for Dynamic Adaptive Genetic Improvement Programming",
- institution = "Computing Science and Mathematics, University of Stirling",
- year = "2014",
- number = "CSM-195",
- address = "UK",
- month = "17 " # jan,
- keywords = "genetic algorithms, genetic programming, Genetic Improvement, Scala",
-
URL = "
http://www.cs.stir.ac.uk/~kjt/techreps/previous.html",
-
URL = "
http://www.cs.stir.ac.uk/~kjt/techreps/pdf/TR195.pdf",
-
URL = "http://www.epitropakis.co.uk/sites/default/files/pubs/genofix-TR.pdf",
-
video_url = "http://crest.cs.ucl.ac.uk/cow/28/videos/COW28_Woodward_240.mp4",
-
video_url = "http://crest.cs.ucl.ac.uk/cow/28/videos/COW28_Woodward_360.mp4",
- size = "12 pages",
- abstract = "Genetic Improvement Programming (GIP) is concerned with automating the burden of software maintenance, the most costly phase of the software life cycle. We describe Gen-O-Fix, a GIP framework which allows a software system hosted on the Java Virtual Machine to be continually improved (e.g. make better predictions; pass more regression tests; reduce power consumption). It is the first exemplar of a dynamic adaptive GIP framework, i.e. it can improve a system as it runs. It is written in the Scala programming language and uses reflection to yield source-to-source transformation. One of the design goals for Gen-O-Fix was to create a tool that is user-centric rather than researcher-centric: the end-user is required only to provide a measure of system quality and the URL of the source code to be improved. We discuss potential applications to predictive, embedded and high-performance systems.",
-
notes = "ISSN 1460-9673
See also slides http://crest.cs.ucl.ac.uk/cow/28/slides/COW28_Woodward.pdf",
