TY - GEN
T1 - Identifying Energy Efficiency Patterns in Sorting Algorithms via Abstract Syntax Tree Mining
AU - Krauss, Oliver
AU - Schuler, Andreas
N1 - Publisher Copyright:
© 2023 The Authors.
PY - 2023
Y1 - 2023
N2 - Energy efficiency is an important topic in the area of mobile computing. Developers are often unaware of the impact their choices on data type use and algorithm design have on this non-functional property. Software energy consumption profiling can be utilized to identify the energy behaviour of implemented methods, while pattern mining can be utilized to identify recurring patterns in the methods being run. We present a methodology to combine energy consumption profiling and discriminative pattern mining to identify energy efficiency patterns. In a study of eight sorting algorithms implemented in Java with the data types int, double and Comparable, profiled on the Android platform, we manage to identify significant patterns in the source code of these 24 implementations. The results show that patterns can be identified for both, the data type in use, and for the energy behaviour of efficient or inefficient sorting algorithms, that explain the observed energy profiles.
AB - Energy efficiency is an important topic in the area of mobile computing. Developers are often unaware of the impact their choices on data type use and algorithm design have on this non-functional property. Software energy consumption profiling can be utilized to identify the energy behaviour of implemented methods, while pattern mining can be utilized to identify recurring patterns in the methods being run. We present a methodology to combine energy consumption profiling and discriminative pattern mining to identify energy efficiency patterns. In a study of eight sorting algorithms implemented in Java with the data types int, double and Comparable, profiled on the Android platform, we manage to identify significant patterns in the source code of these 24 implementations. The results show that patterns can be identified for both, the data type in use, and for the energy behaviour of efficient or inefficient sorting algorithms, that explain the observed energy profiles.
KW - Decision Support Systems
KW - Genetic Algorithms
KW - Knowledge Based Systems
UR - http://www.scopus.com/inward/record.url?scp=85178657710&partnerID=8YFLogxK
U2 - 10.46354/i3m.2023.mas.003
DO - 10.46354/i3m.2023.mas.003
M3 - Conference contribution
AN - SCOPUS:85178657710
T3 - Proceedings of the International Conference on Modeling and Applied Simulation, MAS
BT - 22nd International Conference on Modeling and Applied Simulation, MAS 2023
A2 - Bruzzone, Agostino G.
A2 - De Felice, Fabio
A2 - Longo, Francesco
A2 - Massei, Marina
A2 - Solis, Adriano O.
PB - Cal-Tek srl
T2 - 22nd International Conference on Modeling and Applied Simulation, MAS 2023
Y2 - 18 September 2023 through 20 September 2023
ER -