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.
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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 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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