Created by W.Langdon from gp-bibliography.bib Revision:1.8098
Overall, we found 63 GI papers that use a GI tool to improve non-functional properties of software, within which 31 are accompanied with open-source code. We were able to successfully run nine GI tools, and found that ultimately only two, Gin and PyGGI, can be readily applied to new general software.",
(1) Testing Gin with SAT4J, which is the software improved byPyGGI 2.0 in previous work \cite{blot:2021:tevc}
(2) Testing PyGGI 2.0 with Gson, which is the software improvedby Gin in previous work \cite{Petke:2019:SSBSE}
(3) Testing LocoGP with Gson.
(4) Testing the tool for shader simplification with MiniSAT,which is the software used in previous work on a GISMO-based tool \cite{Petke:2014:EuroGP}
(5) Testing the GISMO-based tool with RNAfold, which is the software improved by GGGP in previous work \cite{Langdon:2017:GI}
(6) Testing the tool for OpenCV with MiniSAT.
(7) Testing GGGP with MiniSAT.
(8) Testing PowerGAUGE with MiniSAT
https://github.com/gintool/gin GIN Maven Gradle
https://github.com/coinse/pyggi
LocoGP
https://github.com/fabianishere/shadevolution
GISMO
OpenCV
GGGP
PowerGAUGE
'Gin and PyGGI are the only two GI tools are application-agnostic and can be easily applied to improve new software.'
GECCO-2022 A Recombination of the 31st International Conference on Genetic Algorithms (ICGA) and the 27th Annual Genetic Programming Conference (GP)",
Genetic Programming entries for Shengjie Zuo Aymeric Blot Justyna Petke