SPELLing out energy leaks: Aiding developers locate energy inefficient code
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Publication Date: | 2020 |
Other Authors: | , , , , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://hdl.handle.net/1822/68729 |
Summary: | Although hardware is generally seen as the main culprit for a computer's energy usage, software too has a tremendous impact on the energy spent. Unfortunately, there is still not enough support for software developers so they can make their code more energy-aware.This paper proposes a technique to detect energy inefficient fragments in the source code of a software system. Test cases are executed to obtain energy consumption measurements, and a statistical method, based on spectrum-based fault localization, is introduced to relate energy consumption to the source code. The result of our technique is an energy ranking of source code fragments pointing developers to possible energy leaks in their code. This technique was implemented in the SPELL toolkit.Finally, in order to evaluate our technique, we conducted an empirical study where we asked participants to optimize the energy efficiency of a software system using our tool, while also having two other groups using no tool assistance and a profiler, respectively. We showed statistical evidence that developers using our technique were able to improve the energy efficiency by 43% on average, and even out performing a profiler for energy optimization. (C) 2019 Elsevier Inc. All rights reserved. |
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SPELLing out energy leaks: Aiding developers locate energy inefficient codeGreen SoftwareProgram AnalysisProgram OptimizationGreen ComputingFault LocalizationEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaScience & TechnologyAlthough hardware is generally seen as the main culprit for a computer's energy usage, software too has a tremendous impact on the energy spent. Unfortunately, there is still not enough support for software developers so they can make their code more energy-aware.This paper proposes a technique to detect energy inefficient fragments in the source code of a software system. Test cases are executed to obtain energy consumption measurements, and a statistical method, based on spectrum-based fault localization, is introduced to relate energy consumption to the source code. The result of our technique is an energy ranking of source code fragments pointing developers to possible energy leaks in their code. This technique was implemented in the SPELL toolkit.Finally, in order to evaluate our technique, we conducted an empirical study where we asked participants to optimize the energy efficiency of a software system using our tool, while also having two other groups using no tool assistance and a profiler, respectively. We showed statistical evidence that developers using our technique were able to improve the energy efficiency by 43% on average, and even out performing a profiler for energy optimization. (C) 2019 Elsevier Inc. All rights reserved.This work is funded by the ERDF -European Regional Development Fund through the Operational Programme for Competitiveness and Internationalization -COMPETE 2020 Programme within project POCI-01-0145-FEDER-006961, and by National Funds through the Portuguese funding agency, FCT -Fundacao para a Ciencia e a Tecnologia within project POCI010145FEDER016718, UID/EEA/50014/2013, and by FCT grant SFRH/BD/132485/2017. This work is also supported by operation Centro010145FEDER000019 -C4 -Centro de Competencias em Cloud Computing, cofinanced by the European Regional Development Fund (ERDF) through the Programa Operacional Regional do Centro (Centro 2020), in the scope of the Sistema de Apoio a Investigacao Cientifica e Tecnologica -Programas Integrados de IC&DT, and the first author was financed by post-doc grant referencia C4_SMDS_L1-1_D.Elsevier Science BVUniversidade do MinhoPereira, Rui Alexandre AfonsoCarção, Tiago AlvesCouto, Marco Domingos MendesCunha, JácomeFernandes, João PauloSaraiva, João20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/68729eng0164-121210.1016/j.jss.2019.110463https://www.sciencedirect.com/science/article/pii/S0164121219302377info: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:RCAAP2025-04-12T05:07:34Zoai:repositorium.sdum.uminho.pt:1822/68729Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:06:05.469435Repositórios 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 |
SPELLing out energy leaks: Aiding developers locate energy inefficient code |
title |
SPELLing out energy leaks: Aiding developers locate energy inefficient code |
spellingShingle |
SPELLing out energy leaks: Aiding developers locate energy inefficient code Pereira, Rui Alexandre Afonso Green Software Program Analysis Program Optimization Green Computing Fault Localization Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática Science & Technology |
title_short |
SPELLing out energy leaks: Aiding developers locate energy inefficient code |
title_full |
SPELLing out energy leaks: Aiding developers locate energy inefficient code |
title_fullStr |
SPELLing out energy leaks: Aiding developers locate energy inefficient code |
title_full_unstemmed |
SPELLing out energy leaks: Aiding developers locate energy inefficient code |
title_sort |
SPELLing out energy leaks: Aiding developers locate energy inefficient code |
author |
Pereira, Rui Alexandre Afonso |
author_facet |
Pereira, Rui Alexandre Afonso Carção, Tiago Alves Couto, Marco Domingos Mendes Cunha, Jácome Fernandes, João Paulo Saraiva, João |
author_role |
author |
author2 |
Carção, Tiago Alves Couto, Marco Domingos Mendes Cunha, Jácome Fernandes, João Paulo Saraiva, João |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Pereira, Rui Alexandre Afonso Carção, Tiago Alves Couto, Marco Domingos Mendes Cunha, Jácome Fernandes, João Paulo Saraiva, João |
dc.subject.por.fl_str_mv |
Green Software Program Analysis Program Optimization Green Computing Fault Localization Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática Science & Technology |
topic |
Green Software Program Analysis Program Optimization Green Computing Fault Localization Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática Science & Technology |
description |
Although hardware is generally seen as the main culprit for a computer's energy usage, software too has a tremendous impact on the energy spent. Unfortunately, there is still not enough support for software developers so they can make their code more energy-aware.This paper proposes a technique to detect energy inefficient fragments in the source code of a software system. Test cases are executed to obtain energy consumption measurements, and a statistical method, based on spectrum-based fault localization, is introduced to relate energy consumption to the source code. The result of our technique is an energy ranking of source code fragments pointing developers to possible energy leaks in their code. This technique was implemented in the SPELL toolkit.Finally, in order to evaluate our technique, we conducted an empirical study where we asked participants to optimize the energy efficiency of a software system using our tool, while also having two other groups using no tool assistance and a profiler, respectively. We showed statistical evidence that developers using our technique were able to improve the energy efficiency by 43% on average, and even out performing a profiler for energy optimization. (C) 2019 Elsevier Inc. All rights reserved. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020 2020-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/68729 |
url |
https://hdl.handle.net/1822/68729 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0164-1212 10.1016/j.jss.2019.110463 https://www.sciencedirect.com/science/article/pii/S0164121219302377 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier Science BV |
publisher.none.fl_str_mv |
Elsevier Science BV |
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