- author = "Saemundur O. Haraldsson and John R. Woodward",
- title = "Automated design of algorithms and genetic improvement: contrast and commonalities",
- booktitle = "GECCO 2014 4th workshop on evolutionary computation for the automated design of algorithms",
- year = "2014",
- editor = "John Woodward and Jerry Swan and Earl Barr",
- pages = "1373--1380",
- month = "12-16 " # jul,
- organisation = "SIGEVO",
- address = "Vancouver, BC, Canada",
- publisher_address = "New York, NY, USA",
- publisher = "ACM",
- keywords = "genetic algorithms, genetic programming, Genetic Improvement, Automated Design of Algorithms (ADA), GI, Abstract Syntax Tree (AST), Search Based Software Engineering, SBSE",
- isbn13 = "978-1-4503-2881-4",
-
URL = "
http://doi.acm.org/10.1145/2598394.2609874",
-
DOI = "
doi:10.1145/2598394.2609874",
- size = "8 pages",
-
abstract = "Automated Design of Algorithms (ADA) and Genetic
Improvement (GI) are two relatively young fields of
research that have been receiving more attention in
recent years. Both methodologies can improve programs
using evolutionary search methods and successfully
produce human competitive programs. ADA and GI are used
for improving functional properties such as quality of
solution and non-functional properties, e.g. speed,
memory and, energy consumption. Only GI of the two has
been used to fix bugs, probably because it is applied
globally on the whole source code while ADA typically
replaces a function or a method locally. While GI is
applied directly to the source code ADA works ex-situ,
i.e. as a separate process from the program it is
improving.
Although the methodologies overlap in many ways they differ on some fundamentals and for further progress to be made researchers from both disciplines should be aware of each other's work.",
-
notes = "Also known as \cite{2609874} Distributed at
GECCO-2014.
Unstable URL at citeseerx.ist.psu.edu",
