- title = "{PyGGI}: {P}ython {G}eneral framework for {G}enetic {I}mprovement",
- author = "Gabin An and Jinhan Kim and Seongmin Lee and Shin Yoo",
- booktitle = "Proceedings of Korea Software Congress",
- year = "2017",
- series = "KSC 2017",
- pages = "536--538",
- address = "Busan, South Korea",
- month = "20-22 " # dec,
- keywords = "genetic algorithms, genetic programming, Genetic Improvement",
-
URL = "
https://coinse.kaist.ac.kr/publications/pdfs/An2017aa.pdf",
-
URL = "
http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE07322214&language=en_EN#",
- size = "3 pages",
- abstract = "We present Python General Framework for Genetic Improvement (PYGGI, pronounced pigi), a lightweight general framework for Genetic Improvement (GI). It is designed to be a simple and easy to configure GI tool for multiple programming languages such as Java, C, or Python. Through two case studies, we show that PYGGI can modify source code of a given program either to improve non-functional properties or to automatically repair functional faults.",
-
notes = "177 20A1A2-5
modification operators: deletion, copying, and replacement of source code as a list of code lines. Local search algorithm. triangle program
http://www.kiise.or.kr/conference/kcc/2017/
https://github.com/coinse/pyggi
Also known as \cite{an:2017:ksc}",
