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Fuzzy Edit Sequences in Genetic Improvement

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 Green open access

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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
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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