Products go green: worst-case energy consumption in software product lines

Bibliographic Details
Main Author: Couto, Marco Domingos Mendes
Publication Date: 2017
Other Authors: Borba, Paulo, Cunha, Jácome Miguel Costa, Fernandes, João Paulo Soares, Pereira, Rui, Saraiva, João
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/1822/65361
Summary: The optimization of software to be (more) energy efficient is becoming a major concern for the software industry. Although several techniques have been presented to measure energy consumption for software, none has addressed software product lines (SPLs). Thus, to measure energy consumption of a SPL, the products must be generated and measured individually, which is too costly.In this paper, we present a technique and a prototype tool to statically estimate the worst case energy consumption for SPL. The goal is to provide developers with techniques and tools to reason about the energy consumption of all products in a SPL, without having to produce, run and measure the energy in all of them.Our technique combines static program analysis techniques and worst case execution time prediction with energy consumption analysis. This technique analyzes all products in a feature-sensitive manner, that is, a feature used in several products is analyzed only once, while the energy consumption is estimated once per product.We implemented our technique in a tool called Serapis. We did a preliminary evaluation using a product line for image processing implemented in C. Our experiments considered 7 products from such line and our initial results show that the tool was able to estimate the worst-case energy consumption with a mean error percentage of 9.4% and standard deviation of 6.2% when compared with the energy measured when running the products.
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spelling Products go green: worst-case energy consumption in software product linesCiências Naturais::Ciências da Computação e da InformaçãoScience & TechnologyThe optimization of software to be (more) energy efficient is becoming a major concern for the software industry. Although several techniques have been presented to measure energy consumption for software, none has addressed software product lines (SPLs). Thus, to measure energy consumption of a SPL, the products must be generated and measured individually, which is too costly.In this paper, we present a technique and a prototype tool to statically estimate the worst case energy consumption for SPL. The goal is to provide developers with techniques and tools to reason about the energy consumption of all products in a SPL, without having to produce, run and measure the energy in all of them.Our technique combines static program analysis techniques and worst case execution time prediction with energy consumption analysis. This technique analyzes all products in a feature-sensitive manner, that is, a feature used in several products is analyzed only once, while the energy consumption is estimated once per product.We implemented our technique in a tool called Serapis. We did a preliminary evaluation using a product line for image processing implemented in C. Our experiments considered 7 products from such line and our initial results show that the tool was able to estimate the worst-case energy consumption with a mean error percentage of 9.4% and standard deviation of 6.2% when compared with the energy measured when running the products.We would like to thank Simao Melo de Sousa (University of Beira Interior) for helpful discussions about the topics of this paper, and to the anonymous reviewers for the valuable comments and feedback. This work is financed by the ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT - Fundacao para a Ciencia e a Tecnologia within project POCI-01-0145-FEDER-016718, and FLAD/NSF under the project with ref. 278/2016.Association for Computing Machinery (ACM)Universidade do MinhoCouto, Marco Domingos MendesBorba, PauloCunha, Jácome Miguel CostaFernandes, João Paulo SoaresPereira, RuiSaraiva, João20172017-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/65361engMarco Couto, Paulo Borba, Jácome Cunha, João Paulo Fernandes, Rui Pereira,and João Saraiva. 2017. Products go Green: Worst-Case Energy Consump-tion in Software Product Lines. InProceedings of SPLC ’17, Sevilla, Spain,September 25-29, 2017,10 pages.DOI: 10.1145/3106195.3106214978145035221510.1145/3106195.3106214info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T06:18:37Zoai:repositorium.sdum.uminho.pt:1822/65361Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T15:48:42.690230Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Products go green: worst-case energy consumption in software product lines
title Products go green: worst-case energy consumption in software product lines
spellingShingle Products go green: worst-case energy consumption in software product lines
Couto, Marco Domingos Mendes
Ciências Naturais::Ciências da Computação e da Informação
Science & Technology
title_short Products go green: worst-case energy consumption in software product lines
title_full Products go green: worst-case energy consumption in software product lines
title_fullStr Products go green: worst-case energy consumption in software product lines
title_full_unstemmed Products go green: worst-case energy consumption in software product lines
title_sort Products go green: worst-case energy consumption in software product lines
author Couto, Marco Domingos Mendes
author_facet Couto, Marco Domingos Mendes
Borba, Paulo
Cunha, Jácome Miguel Costa
Fernandes, João Paulo Soares
Pereira, Rui
Saraiva, João
author_role author
author2 Borba, Paulo
Cunha, Jácome Miguel Costa
Fernandes, João Paulo Soares
Pereira, Rui
Saraiva, João
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Couto, Marco Domingos Mendes
Borba, Paulo
Cunha, Jácome Miguel Costa
Fernandes, João Paulo Soares
Pereira, Rui
Saraiva, João
dc.subject.por.fl_str_mv Ciências Naturais::Ciências da Computação e da Informação
Science & Technology
topic Ciências Naturais::Ciências da Computação e da Informação
Science & Technology
description The optimization of software to be (more) energy efficient is becoming a major concern for the software industry. Although several techniques have been presented to measure energy consumption for software, none has addressed software product lines (SPLs). Thus, to measure energy consumption of a SPL, the products must be generated and measured individually, which is too costly.In this paper, we present a technique and a prototype tool to statically estimate the worst case energy consumption for SPL. The goal is to provide developers with techniques and tools to reason about the energy consumption of all products in a SPL, without having to produce, run and measure the energy in all of them.Our technique combines static program analysis techniques and worst case execution time prediction with energy consumption analysis. This technique analyzes all products in a feature-sensitive manner, that is, a feature used in several products is analyzed only once, while the energy consumption is estimated once per product.We implemented our technique in a tool called Serapis. We did a preliminary evaluation using a product line for image processing implemented in C. Our experiments considered 7 products from such line and our initial results show that the tool was able to estimate the worst-case energy consumption with a mean error percentage of 9.4% and standard deviation of 6.2% when compared with the energy measured when running the products.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-01-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/65361
url http://hdl.handle.net/1822/65361
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Marco Couto, Paulo Borba, Jácome Cunha, João Paulo Fernandes, Rui Pereira,and João Saraiva. 2017. Products go Green: Worst-Case Energy Consump-tion in Software Product Lines. InProceedings of SPLC ’17, Sevilla, Spain,September 25-29, 2017,10 pages.DOI: 10.1145/3106195.3106214
9781450352215
10.1145/3106195.3106214
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Association for Computing Machinery (ACM)
publisher.none.fl_str_mv Association for Computing Machinery (ACM)
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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repository.mail.fl_str_mv info@rcaap.pt
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