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Evolving better software parameters

Langdon, WB; Petke, J; (2018) Evolving better software parameters. In: Colanzi, T and McMinn, P, (eds.) Search-Based Software Engineering. SSBSE 2018. Lecture Notes in Computer Science. (pp. pp. 363-369). Springer: Cham. Green open access

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Abstract

Genetic improvement might be widely used to adapt existing numerical values within programs. Applying GI to embedded parameters in computer code can create new functionality. For example, CMA-ES can evolve 1024 real numbers in a GNU C library square root to implement a cube root routine for C.

Type: Proceedings paper
Title: Evolving better software parameters
Event: International Symposium on Search Based Software Engineering
ISBN-13: 9783319992402
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-99241-9_22
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Genetic improvement · SBSE · GGGP Software maintenance of empirical constants · Data transplantation glibc · sqrt · cbrt
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/10056892
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