Blot, A;
(2019)
Fuzzy Edit Sequences in Genetic Improvement.
In:
Proceedings of the 2019 IEEE/ACM International Workshop on Genetic Improvement (GI).
(pp. pp. 30-31).
IEEE
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Abstract
Genetic improvement uses automated search to find improved versions of existing software. Edit sequences have been proposed as a very convenient way to represent code modifications, focusing on the changes themselves rather than duplicating the entire program. However, edits are usually defined in terms of practical operations rather than in terms of semantic changes; indeed, crossover and other edit sequence mutations usually never guarantee semantic preservation. We propose several changes to usual edit sequences, specifically augmenting edits with content data and using fuzzy matching, in an attempt to improve semantic preservation.
Type: | Proceedings paper |
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Title: | Fuzzy Edit Sequences in Genetic Improvement |
Event: | 2019 IEEE/ACM International Workshop on Genetic Improvement (GI) |
Location: | Montreal (QC), Canada |
Dates: | 28th May 2019 |
ISBN-13: | 978-1-7281-2268-7 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1109/GI.2019.00016 |
Publisher version: | https://doi.org/10.1109/GI.2019.00016 |
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: | Genetics, Semantics, Software, Bars, Maintenance engineering, Software engineering, Programming |
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/10084603 |
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