Title :
Optimizing Existing Software With Genetic Programming
Author :
Langdon, William B. ; Harman, Mark
Author_Institution :
Dept. of Comput. Sci., Univ. Coll. London, London, UK
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);
Journal_Title :
Evolutionary Computation, IEEE Transactions on
DOI :
10.1109/TEVC.2013.2281544
