DocumentCode
1758433
Title
Optimizing Existing Software With Genetic Programming
Author
Langdon, William B. ; Harman, Mark
Author_Institution
Dept. of Comput. Sci., Univ. Coll. London, London, UK
Volume
19
Issue
1
fYear
2015
fDate
Feb. 2015
Firstpage
118
Lastpage
135
Abstract
We show that the genetic improvement of programs (GIP) can scale by evolving increased performance in a widely-used and highly complex 50000 line system. Genetic improvement of software for multiple objective exploration (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.
Keywords
genetic algorithms; software engineering; GIP; GISMOE; genetic improvement of programs; genetic improvement of software for multiple objective exploration; genetic programming; software optimization; Complexity theory; DNA; Genetic programming; Grammar; Semantics; Software; ${rm Bowtie2}^{GP}$; Automatic software reengineering; genetic programming (GP); multiple objective exploration; search based software engineering (SBSE);
fLanguage
English
Journal_Title
Evolutionary Computation, IEEE Transactions on
Publisher
ieee
ISSN
1089-778X
Type
jour
DOI
10.1109/TEVC.2013.2281544
Filename
6733370
Link To Document