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Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Code Synthesis in Self-improving Software Systems
AU - Rodrigues Filho, Roberto
AU - Wild, Alexander
AU - Porter, Barry
N1 - ©2019 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PY - 2019/8/8
Y1 - 2019/8/8
N2 - This paper aims at provoking a wide discussion around code synthesis and its importance in creating the next generation of self-improving software systems. As a starting point for the discussion, a machine-to-machine self-improving framework is presented. The framework aims at improving system's performance by integrating two modules: i) a self improving online module, and ii) a code synthesiser offline module. The online module learns, at runtime, as it handles the system’s inputs, how to best compose the system from a pallet ofavailable software components and a user-defined high level goal. The offline code synthesiser generates new components based on the perceived system’s input, executing environment and the system’s goal provided by the online module. The code synthesiser then provides better component options for the online module to integrate with the system to improve its performance. The paper describes the framework, focusing on its main challenges.
AB - This paper aims at provoking a wide discussion around code synthesis and its importance in creating the next generation of self-improving software systems. As a starting point for the discussion, a machine-to-machine self-improving framework is presented. The framework aims at improving system's performance by integrating two modules: i) a self improving online module, and ii) a code synthesiser offline module. The online module learns, at runtime, as it handles the system’s inputs, how to best compose the system from a pallet ofavailable software components and a user-defined high level goal. The offline code synthesiser generates new components based on the perceived system’s input, executing environment and the system’s goal provided by the online module. The code synthesiser then provides better component options for the online module to integrate with the system to improve its performance. The paper describes the framework, focusing on its main challenges.
U2 - 10.1109/FAS-W.2019.00015
DO - 10.1109/FAS-W.2019.00015
M3 - Conference contribution/Paper
SN - 9781728124070
SP - 4
EP - 5
BT - International Workshop of Self-Improving System Integration
PB - IEEE
ER -