Gin: Genetic improvement research made easy
Date
2019
Authors
Brownlee, A.E.I.
Petke, J.
Alexander, B.
Barr, E.T.
Wagner, M.
White, D.R.
Editors
LopezIbanez, M.
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
GECCO 2019: Proceedings of the 2019 Genetic and Evolutionary Computation Conference, 2019 / LopezIbanez, M. (ed./s), pp.985-993
Statement of Responsibility
Alexander E. I. Brownlee, Justyna Petke, Brad Alexander, Earl T. Barr, Markus Wagner, David R. White
Conference Name
Genetic and Evolutionary Computation Conference (GECCO) (13 Jul 2019 - 17 Jul 2019 : Prague, Czech Republic)
Abstract
Genetic improvement (GI) is a young field of research on the cusp of transforming software development. GI uses search to improve existing software. Researchers have already shown that GI can improve human-written code, ranging from program repair to optimising run-time, from reducing energy-consumption to the transplantation of new functionality. Much remains to be done. The cost of re-implementing GI to investigate new approaches is hindering progress. Therefore, we present Gin, an extensible and modifiable toolbox for GI experimentation, with a novel combination of features. Instantiated in Java and targeting the Java ecosystem, Gin automatically transforms, builds, and tests Java projects. Out of the box, Gin supports automated test-generation and source code profiling. We show, through examples and a case study, how Gin facilitates experimentation and will speed innovation in GI.
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Dissertation Note
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Rights
© 2019 Copyright held by the owner/author(s). Publication rights licensed to the Association for Computing Machinery.