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Conference Proceeding

Gin: Genetic Improvement Research Made Easy

Citation
Brownlee AEI, Petke J, Alexander B, Barr ET, Wagner M & White DR (2019) Gin: Genetic Improvement Research Made Easy. In: GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO 2019: The Genetic and Evolutionary Computation Conference, Prague, Czech Republic, 13.07.2019-17.07.2019. New York: ACM, pp. 985-993. https://doi.org/10.1145/3321707.3321841

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.

Keywords
Genetic Improvement; GI; Search-based Software Engineering; SBSE

StatusPublished
Author(s)Brownlee, Alexander E I; Petke, Justyna; Alexander, Brad; Barr, Earl T; Wagner, Markus; White, David R.
Publication date31/07/2019
Publication date online31/07/2019
URLhttp://hdl.handle.net/1893/29352
PublisherACM
Place of publicationNew York
ISBN978-1-4503-6111-8
ConferenceGECCO 2019: The Genetic and Evolutionary Computation Conference
Conference locationPrague, Czech Republic
Dates
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