TY  - GEN
ID  - discovery10176410
Y1  - 2023///
UR  - https://doi.org/10.1109/GI59320.2023.00011
A1  - Langdon, WB
A1  - Alexander, BJ
PB  - Institute of Electrical and Electronics Engineers (IEEE)
KW  - Genetic programming
KW  -  GP
KW  -  linear representation
KW  -  SBSE
KW  -  software resilience
KW  -  automatic code customisation
KW  - 
world wide location
KW  -  plus codes
KW  -  zip code
AV  - public
N2  - Magpie (Machine Automated General Performance Improvement via Evolution of software) has been recently developed by Aymeric Blot from PyGGI 2.0. Like PyGGI, it claims to be able to optimise computer source code written in arbitrary programming languages. So far it has been demonstrated on benchmarks written in Python and C. Recently we have used hill climbing to customise two industrial open source programs: Google's Open Location Code OLC and Uber's Hexagonal Hierarchical Spatial Index H3 [W. B. Langdon et al., 'Genetic improvement of LLVM intermediate representation', in EuroGP 2023]. Magpie found much faster improvements (reducing instruction counts by up to 15% v. 2%) which generalise. Various glitches in Magpie are also reported.
SP  - 9
EP  - 16
TI  - Genetic Improvement of OLC and H3 with Magpie
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
ER  -