- author = "William B. Langdon and Vesna Nowack and Justyna Petke and Erik M. Fredericks and Gabin An and Aymeric Blot and Markus Wagner and Hyeonseok Lee",
- title = "{Genetic Improvement @ ICSE 2023}",
- journal = "SIGSOFT Software Engineering Notes",
- year = "2023",
- volume = "48",
- number = "4",
- month = oct,
- pages = "51--59",
- keywords = "genetic algorithms, genetic programming, genetic improvement, AI, copilot, ANN, LLM, automatic testing, RAM reduction, novelty search, cloud computing cost reduction, CROP software dataset, QuixBugs, hypertesting, hyper-parameters",
- publisher = "Association for Computing Machinery",
- ISSN = "0163-5948",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/gi2023_sen.pdf",
-
URL = "
https://dl.acm.org/doi/pdf/10.1145/3617946.3617956",
-
DOI = "
10.1145/3617946.3617956",
-
video_url = "https://www.youtube.com/playlist?list=PLI8fiFpB7BoJLh6cUpGBjyeB1hM9DET1V",
- size = "9 pages",
- abstract = "Following the formal presentations, which included keynotes by Prof. Myra B. Cohen of Iowa State University and Dr. Sebastian Baltes of SAP as well as six papers (which are recorded in the proceedings) there was a wide ranging discussion at the twelfth international Genetic Improvement workshop, GI-2023 @ ICSE held on Saturday May 20, 2023 in Melbourne and online via Zoom. Topics included GI to improve testing, and remove unpleasant surprises in cloud computing costs, incorporating novelty search, large language models (LLM ANN) and GI benchmarks.",
-
notes = "GI @ ICSE 2023 ACM SIGSOFT Software Engineering Notes
https://dl.acm.org/newsletter/sigsoft/
See also \cite{Nowack:2023:GI}",
