Langdon, WB;
White, DR;
Harman, M;
Jia, Y;
Petke, J;
(2016)
API-constrained genetic improvement.
In: Sarro, F and Deb, K, (eds.)
Search Based Software Engineering: 8th International Symposium, SSBSE 2016, Raleigh, NC, USA, October 8-10, 2016, Proceedings.
(pp. pp. 224-230).
Springer International Publishing
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Abstract
ACGI respects the Application Programming Interface whilst using genetic programming to optimise the implementation of the API. It reduces the scope for improvement but it may smooth the path to GI acceptance because the programmer’s code remains unaffected; only library code is modified.We applied ACGI to C++ software for the stateof-the-art OpenCV SEEDS superPixels image segmentation algorithm, obtaining a speed-up of up to 13.2% (±1.3%) to the $50K Challenge winner announced at CVPR 2015.
| Type: | Proceedings paper |
|---|---|
| Title: | API-constrained genetic improvement |
| Event: | SSBSE 2016: 8th International Symposium, 8-10 October 2016, Raleigh, NC, USA |
| ISBN-13: | 9783319471051 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-319-47106-8_16 |
| Publisher version: | http://link.springer.com/chapter/10.1007%2F978-3-3... |
| Language: | English |
| Additional information: | Copyright © Springer International Publishing AG 2016. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-47106-8_16 |
| 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.ucl.ac.uk/id/eprint/1524244 |
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