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Synthetic Benchmarks for Genetic Improvement

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 Green open access

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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 > 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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