GIN: genetic improvement research made easy

Alexander E.I. Brownlee, Earl T. Barr, Justyna Petke, Markus Wagner, Brad Alexander, David R. White

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

33 Citations (Scopus)


Genetic improvement (GI) is a young ield 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 modiiable 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 proiling. We show, through examples and a case study, how Gin facilitates experimentation and will speed innovation in GI.

Original languageEnglish
Title of host publicationProceedings of the 2019 Genetic and Evolutionary Computation Conference
EditorsAnne Auger, Thomas Stützle
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages9
ISBN (Electronic)9781450361118
Publication statusPublished - 2019
Externally publishedYes
EventThe Genetic and Evolutionary Computation Conference 2019 - Prague, Czechia
Duration: 13 Jul 201917 Jul 2019
Conference number: 21st (Proceedings)


ConferenceThe Genetic and Evolutionary Computation Conference 2019
Abbreviated titleGECCO 2019
Internet address


  • Genetic Improvement
  • GI
  • SBSE
  • Search-based Software Engineering

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