Identifying Energy Efficiency Patterns in Sorting Algorithms via Abstract Syntax Tree Mining

Oliver Krauss; Andreas Schuler

doi:10.46354/i3m.2023.mas.003

Identifying Energy Efficiency Patterns in Sorting Algorithms via Abstract Syntax Tree Mining

Oliver Krauss^*
, Andreas Schuler

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	22nd International Conference on Modeling and Applied Simulation, MAS 2023
Editors	Agostino G. Bruzzone, Fabio De Felice, Francesco Longo, Marina Massei, Adriano O. Solis
Publisher	Cal-Tek srl
ISBN (Electronic)	9788885741928
DOIs	https://doi.org/10.46354/i3m.2023.mas.003
Publication status	Published - 2023
Event	22nd International Conference on Modeling and Applied Simulation, MAS 2023 - Athens, Greece Duration: 18 Sept 2023 → 20 Sept 2023

Publication series

Name	Proceedings of the International Conference on Modeling and Applied Simulation, MAS
Volume	2023-September
ISSN (Print)	2724-0037

Conference

Conference	22nd International Conference on Modeling and Applied Simulation, MAS 2023
Country/Territory	Greece
City	Athens
Period	18.09.2023 → 20.09.2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Decision Support Systems
Genetic Algorithms
Knowledge Based Systems

Access to Document

10.46354/i3m.2023.mas.003

Cite this

Krauss, O., & Schuler, A. (2023). Identifying Energy Efficiency Patterns in Sorting Algorithms via Abstract Syntax Tree Mining. In A. G. Bruzzone, F. De Felice, F. Longo, M. Massei, & A. O. Solis (Eds.), 22nd International Conference on Modeling and Applied Simulation, MAS 2023 (Proceedings of the International Conference on Modeling and Applied Simulation, MAS; Vol. 2023-September). Cal-Tek srl. https://doi.org/10.46354/i3m.2023.mas.003

Krauss, Oliver ; Schuler, Andreas. / Identifying Energy Efficiency Patterns in Sorting Algorithms via Abstract Syntax Tree Mining. 22nd International Conference on Modeling and Applied Simulation, MAS 2023. editor / Agostino G. Bruzzone ; Fabio De Felice ; Francesco Longo ; Marina Massei ; Adriano O. Solis. Cal-Tek srl, 2023. (Proceedings of the International Conference on Modeling and Applied Simulation, MAS).

@inproceedings{ed0319b79e8749448af332fdb505d8bf,

title = "Identifying Energy Efficiency Patterns in Sorting Algorithms via Abstract Syntax Tree Mining",

abstract = "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.",

keywords = "Decision Support Systems, Genetic Algorithms, Knowledge Based Systems",

author = "Oliver Krauss and Andreas Schuler",

note = "Publisher Copyright: {\textcopyright} 2023 The Authors.; 22nd International Conference on Modeling and Applied Simulation, MAS 2023 ; Conference date: 18-09-2023 Through 20-09-2023",

year = "2023",

doi = "10.46354/i3m.2023.mas.003",

language = "English",

series = "Proceedings of the International Conference on Modeling and Applied Simulation, MAS",

publisher = "Cal-Tek srl",

editor = "Bruzzone, \{Agostino G.\} and \{De Felice\}, Fabio and Francesco Longo and Marina Massei and Solis, \{Adriano O.\}",

booktitle = "22nd International Conference on Modeling and Applied Simulation, MAS 2023",

}

Krauss, O & Schuler, A 2023, Identifying Energy Efficiency Patterns in Sorting Algorithms via Abstract Syntax Tree Mining. in AG Bruzzone, F De Felice, F Longo, M Massei & AO Solis (eds), 22nd International Conference on Modeling and Applied Simulation, MAS 2023. Proceedings of the International Conference on Modeling and Applied Simulation, MAS, vol. 2023-September, Cal-Tek srl, 22nd International Conference on Modeling and Applied Simulation, MAS 2023, Athens, Greece, 18.09.2023. https://doi.org/10.46354/i3m.2023.mas.003

Identifying Energy Efficiency Patterns in Sorting Algorithms via Abstract Syntax Tree Mining. / Krauss, Oliver; Schuler, Andreas.
22nd International Conference on Modeling and Applied Simulation, MAS 2023. ed. / Agostino G. Bruzzone; Fabio De Felice; Francesco Longo; Marina Massei; Adriano O. Solis. Cal-Tek srl, 2023. (Proceedings of the International Conference on Modeling and Applied Simulation, MAS; Vol. 2023-September).

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

TY - GEN

T1 - Identifying Energy Efficiency Patterns in Sorting Algorithms via Abstract Syntax Tree Mining

AU - Krauss, Oliver

AU - Schuler, Andreas

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 - https://www.scopus.com/pages/publications/85178657710

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 -

Krauss O, Schuler A. Identifying Energy Efficiency Patterns in Sorting Algorithms via Abstract Syntax Tree Mining. In Bruzzone AG, De Felice F, Longo F, Massei M, Solis AO, editors, 22nd International Conference on Modeling and Applied Simulation, MAS 2023. Cal-Tek srl. 2023. (Proceedings of the International Conference on Modeling and Applied Simulation, MAS). doi: 10.46354/i3m.2023.mas.003

Identifying Energy Efficiency Patterns in Sorting Algorithms via Abstract Syntax Tree Mining

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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