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Genetic Improvement of Software: a Comprehensive Survey

Petke, J; Haraldsson, S; Harman, M; langdon, W; White, D; Woodward, J; (2018) Genetic Improvement of Software: a Comprehensive Survey. IEEE Transactions on Evolutionary Computation , 22 (3) pp. 415-432. 10.1109/TEVC.2017.2693219. Green open access

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Abstract

Genetic improvement (GI) uses automated search to find improved versions of existing software. We present a comprehensive survey of this nascent field of research with a focus on the core papers in the area published between 1995 and 2015. We identified core publications including empirical studies, 96% of which use evolutionary algorithms (genetic programming in particular). Although we can trace the foundations of GI back to the origins of computer science itself, our analysis reveals a significant upsurge in activity since 2012. GI has resulted in dramatic performance improvements for a diverse set of properties such as execution time, energy and memory consumption, as well as results for fixing and extending existing system functionality. Moreover, we present examples of research work that lies on the boundary between GI and other areas, such as program transformation, approximate computing, and software repair, with the intention of encouraging further exchange of ideas between researchers in these fields.

Type: Article
Title: Genetic Improvement of Software: a Comprehensive Survey
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TEVC.2017.2693219
Publisher version: http://dx.doi.org/10.1109/TEVC.2017.2693219
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/10038273
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