Basios, M;
Li, L;
Wu, F;
Kanthan, L;
Barr, ET;
(2017)
Optimising Darwinian Data Structures on Google Guava.
In: Menzies, T and Petke, J, (eds.)
9th International Symposium on Search Based Software Engineering (SSBSE) 2017. Lecture Notes in Computer Science.
(pp. pp. 161-167).
Springer: Cham.
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Abstract
Data structure selection and tuning is laborious but can vastly improve application performance and memory footprint. In this paper, we demonstrate how artemis, a multiobjective, cloud-based optimisation framework can automatically find optimal, tuned data structures and how it is used for optimising the Guava library. From the proposed solutions that artemis found, 27.45% of them improve all measures (execution time, CPU usage, and memory consumption). More specifically, artemis managed to improve the memory consumption of Guava by up 13%, execution time by up to 9%, and 4% CPU usage.
Type: | Proceedings paper |
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Title: | Optimising Darwinian Data Structures on Google Guava |
Event: | 9th International Symposium on Search Based Software Engineering (SSBSE) |
Location: | Paderborn, GERMANY |
Dates: | 09 September 2017 - 11 September 2017 |
ISBN-13: | 978-3-319-66298-5 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1007/978-3-319-66299-2_14 |
Publisher version: | https://doi.org/10.1007/978-3-319-66299-2_14 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Search-based software engineering; Genetic improvement; Software analysis and optimisation; Multi-objective optimisation |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10062895 |
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