Blot, A;
Petke, J;
(2020)
Stack-Based Genetic Improvement.
In:
ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops.
(pp. pp. 289-290).
ACM
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Abstract
Genetic improvement (GI) uses automated search to find improved versions of existing software. If originally GI directly evolved populations of software, most GI work nowadays use a solution representation based on a list of mutations. This representation however has some limitations, notably in how genetic material can be re-combined. We introduce a novel stack-based representation and discuss its possible benefits.
| Type: | Proceedings paper |
|---|---|
| Title: | Stack-Based Genetic Improvement |
| Event: | ICSE '20 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3387940.3392174 |
| Publisher version: | https://doi.org/10.1145/3387940.3392174 |
| 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. |
| 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/10113441 |
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