Darwinian Data Structure Selection
Created by W.Langdon from
gp-bibliography.bib Revision:1.5628
- @InProceedings{Basios:2018:FSE,
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author = "Michail Basios and Lingbo Li and Fan Wu and
Leslie Kanthan and Earl T. Barr",
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title = "Darwinian Data Structure Selection",
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booktitle = "Proceedings of the 2018 26th ACM Joint Meeting on
European Software Engineering Conference and Symposium
on the Foundations of Software Engineering, ESEC/FSE
2018",
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year = "2018",
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editor = "Gary T. Leavens and Alessandro Garcia and
Corina S. Pasareanu",
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pages = "118--128",
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address = "Lake Buena Vista, FL, USA",
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month = "4-9 " # nov,
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publisher = "ACM",
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keywords = "genetic algorithms, genetic programming, Genetic
Improvement, Search-based Software Engineering, SBSE,
Software Analysis and Optimisation",
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isbn13 = "978-1-4503-5573-5",
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URL = "
http://human-competitive.org/sites/default/files/artemis.pdf",
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DOI = "
doi:10.1145/3236024.3236043",
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acmid = "3236043",
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size = "11 pages",
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abstract = "Data structure selection and tuning is laborious but
can vastly improve an applications performance and
memory footprint. Some data structures share a common
interface and enjoy multiple implementations. We call
them Darwinian Data Structures (DDS), since we can
subject their implementations to survival of the
fittest. We introduce ARTEMIS a multi-objective,
cloud-based search-based optimisation framework that
automatically finds optimal, tuned DDS modulo a test
suite, then changes an application to use that DDS.
ARTEMIS achieves substantial performance improvements
for every project in 5 Java projects from DaCapo
benchmark, 8 popular projects and 30 uniformly sampled
projects from GitHub. For execution time, CPU usage,
and memory consumption, ARTEMIS finds at least one
solution that improves all measures for 86percent
(37/43) of the projects. The median improvement across
the best solutions is 4.8percent, 10.1percent,
5.1percent for runtime, memory and CPU usage.
These aggregate results understate ARTEMIS...",
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notes = "Bronze winner 2019 Humies. Slides:
http://www.human-competitive.org/sites/default/files/basiosslides.pptx
Also known as \cite{Basios:2018:DDS:3236024.3236043}",
- }
Genetic Programming entries for
Michail Basios
Lingbo Li
Fan Wu
Leslie Kanthan
Earl Barr
Citations