- author = "Afsoon Afzal and Jeremy Lacomis and Claire {Le Goues} and Christopher Steven Timperley",
- title = "A {Turing} Test for Genetic Improvement",
- booktitle = "GI-2018, ICSE workshops proceedings",
- year = "2018",
- editor = "Justyna Petke and Kathryn Stolee and William B. Langdon and Westley Weimer",
- pages = "17--18",
- address = "Gothenburg, Sweden",
- month = "2 " # jun,
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- keywords = "genetic algorithms, genetic programming, genetic improvement",
- isbn13 = "978-1-4503-5753-1",
-
URL = "
http://dx.doi.org/10.1145/3194810.3194817",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/icse2018/gi2018/papers/Timperley_2018_GI.pdf",
-
URL = "https://afsafzal.github.io/materials/AfzalTuringTest2018.pdf",
-
DOI = "
10.1145/3194810.3194817",
- size = "2 pages",
- abstract = "Genetic improvement is a research field that aims to develop searchbased techniques for improving existing code. GI has been used to automatically repair bugs, reduce energy consumption, and to improve run-time performance. In this paper, we reflect on the often-overlooked relationship between GI and developers within the context of continually evolving software systems. We introduce a distinction between transparent and opaque patches based on intended lifespan and developer interaction. Finally, we outline a Turing test for assessing the ability of a GI system to produce opaque patches that are acceptable to humans. This motivates research into the role GI systems will play in transparent development contexts.",
-
notes = "Note author order change. GI-2018
http://geneticimprovementofsoftware.com/events/papers#icse2018
part of \cite{Petke:2018:ICSEworkshop}",
