Blot, A;
Petke, J;
(2020)
Synthetic Benchmarks for Genetic Improvement.
In:
ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops.
(pp. pp. 287-288).
ACM
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Abstract
Genetic improvement (GI) uses automated search to find improved versions of existing software. If over the years the potential of many GI approaches have been demonstrated, the intrinsic cost of evaluating real-world software makes comparing these approaches in large-scale meta-analyses very expensive. We propose and describe a method to construct synthetic GI benchmarks, to circumvent this bottleneck and enable much faster quality assessment of GI approaches.
| Type: | Proceedings paper |
|---|---|
| Title: | Synthetic Benchmarks for Genetic Improvement |
| Event: | ICSE '20 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3387940.3392175 |
| Publisher version: | https://doi.org/10.1145/3387940.3392175 |
| 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/10113440 |
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