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
(JVM) 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 = "Scalar offers: OO functional language which
'generalises Hindley-Milner type-inference .. to
include sub-typing' Homoiconicity reify expr eval, on
the fly execution. Mutation can use reflection to find
scope of variable (to avoid out of scope errors). Use
pattern matching for many point mutations to AST,
'complex transformations such as context-aware
recombination/mutation.' 'Implicit Conversions..
CamperVan for Car'. '..improve any JVM-hosted system,
irrespective of whether it was originally written is
Scala.' Akka actor fork-join model for the (non)
Halting Problem.
ISSN 1460-9673
See also slides
http://crest.cs.ucl.ac.uk/cow/28/slides/COW28_Woodward.pdf",