research-article

Software energy profiling: comparing releases of a software product

Authors:

Erik A. Jagroep,

Jan Martijn van der Werf,

Sjaak Brinkkemper,

Giuseppe Procaccianti,

Rob van VlietAuthors Info & Claims

ICSE '16: Proceedings of the 38th International Conference on Software Engineering Companion

Pages 523 - 532

https://doi.org/10.1145/2889160.2889216

Published: 14 May 2016 Publication History

Abstract

In the quest for energy efficiency of Information and Communication Technology, so far research has mostly focused on the role of hardware. However, as hardware technology becomes more sophisticated, the role of software becomes crucial. Recently, the impact of software on energy consumption has been acknowledged as significant by researchers in software engineering. In spite of that, measuring the energy consumption of software has proven to be a challenge, due to the large number of variables that need to be controlled to obtain reliable measurements. Due to cost and time constraints, many software product organizations are unable to effectively measure the energy consumption of software. This prevents them to be in control over the energy efficiency of their products.

In this paper, we propose a software energy profiling method to reliably compare the energy consumed by a software product across different releases, from the perspective of a software organization. Our method allows to attribute differences in energy consumption to changes in the software. We validate our profiling method through an empirical experiment on two consecutive releases of a commercial software product. We demonstrate how the method can be applied by organizations and provide an analysis of the software related changes in energy consumption. Our results show that, despite a lack of precise measurements, energy consumption differences between releases of a software product can be quantified down to the level of individual processes. Additionally, the results provide insights on how specific software changes might affect energy consumption.

References

[1]

C. Becker, R. Chitchyan, L. Duboc, S. Easterbrook, B. Penzenstadler, N. Seyff, and C. Venters. Sustainability Design and Software: The Karlskrona Manifesto. In Software Engineering (ICSE), 2015 IEEE/ACM 37th IEEE International Conference on, volume 2, pages 467--476. IEEE, May 2015.

Digital Library

[2]

P. Bozzelli, Q. Gu, and P. Lago. A systematic literature review on green software metrics. Technical report, Technical Report: VU University Amsterdam, 2013.

[3]

H. Chen, B. Luo, and W. Shi. Anole: A case for energy-aware mobile application design. In Parallel Processing Workshops (ICPPW), 2012 41st International Conference on, pages 232--238, 2012.

Digital Library

[4]

C. Ebert and S. Brinkkemper. Software product management - an industry evaluation. Journal of Systems and Software, 95(0):10--18, 2014.

Digital Library

[5]

A. M. Ferreira and B. Pernici. Managing the complex data center environment: an integrated energy-aware framework. Computing, pages 1--41, 2014.

[6]

M. A. Ferreira, E. Hoekstra, B. Merkus, B. Visser, and J. Visser. Seflab: A lab for measuring software energy footprints. In GREENS, pages 30--37. IEEE, May 2013.

Digital Library

[7]

K. Grosskop and J. Visser. Identification of application-level energy optimizations. Proceeding of ICT for Sustainability (ICT4S), pages 101--107, 2013.

[8]

A. Gupta, T. Zimmermann, C. Bird, N. Nagappan, T. Bhat, and S. Emran. Detecting energy patterns in software development. Microsoft Research Microsoft Corporation One Microsoft Way Redmond, WA, 98052, 2011.

[9]

A. Hindle. Green mining: a methodology of relating software change and configuration to power consumption. Empirical Software Engineering, pages 1--36, 2013.

Digital Library

[10]

A. Hindle, A. Wilson, K. Rasmussen, E. J. Barlow, J. C. Campbell, and S. Romansky. Greenminer: A hardware based mining software repositories software energy consumption framework. In Proceedings of the 11th Working Conference on Mining Software Repositories, MSR 2014, pages 12--21, New York, NY, USA, 2014. ACM.

Digital Library

[11]

E. Jagroep, J. M. E. M. van der Werf, S. Jansen, M. Ferreira, and J. Visser. Profiling energy profilers. In Proceedings of the 30th Annual ACM Symposium on Applied Computing, pages 2198--2203. ACM, 2015.

Digital Library

[12]

E. A. Jagroep, J. M. E. M. van der Werf, R. Spauwen, L. Blom, R. van Vliet, and S. Brinkkemper. An energy consumption perspective on software architecture. In 9th European Conference on Software Architecture, number 9278 in LNCS, pages 239--247. Springer, 2015.

[13]

S. Jansen, S. Brinkkemper, J. Souer, and L. Luinenburg. Shades of gray: Opening up a software producing organization with the open software enterprise model. Journal of Systems and Software, 85(7):1495--1510, 2012.

Digital Library

[14]

N. Juristo and A. M. Moreno. Basics of Software Engineering Experimentation. Springer Publishing Company, Incorporated, 1st edition, 2010.

Digital Library

[15]

G. Kalaitzoglou, M. Bruntink, and J. Visser. A practical model for evaluating the energy efficiency of software applications. In ICT for Sust. 2014 (ICT4S-14). Atlantis Press, 2014.

[16]

A. Kansal, F. Zhao, J. Liu, N. Kothari, and A. A. Bhattacharya. Virtual machine power metering and provisioning. In Proceedings of the 1st ACM Symposium on Cloud Computing, SoCC '10, pages 39--50, New York, NY, USA, 2010. ACM.

Digital Library

[17]

B. A. Kitchenham, S. L. Pfleeger, L. M. Pickard, P. W. Jones, D. C. Hoaglin, K. E. Emam, and J. Rosenberg. Preliminary guidelines for empirical research in software engineering. IEEE Transactions on Software Engineering, 28(8):721--734, 2002.

Digital Library

[18]

P. Lago, R. Kazman, N. Meyer, M. Morisio, H. A. Müller, F. Paulisch, G. Scanniello, B. Penzenstadler, and O. Zimmermann. Exploring initial challenges for green software engineering: summary of the first GREENS workshop, at ICSE 2012. ACM SIGSOFT Software Engineering Notes, 38(1):31--33, 2013.

Digital Library

[19]

D. Li, S. Hao, W. G. J. Halfond, and R. Govindan. Calculating source line level energy information for android applications. In Proceedings of the 2013 International Symposium on Software Testing and Analysis, ISSTA 2013, pages 78--89, New York, NY, USA, 2013. ACM.

Digital Library

[20]

Y. Liu, C. Xu, and S.-C. Cheung. Characterizing and detecting performance bugs for smartphone applications. In Proceedings of the 36th International Conference on Software Engineering, pages 1013--1024. ACM, 2014.

Digital Library

[21]

R. Mittal, A. Kansal, and R. Chandra. Empowering developers to estimate app energy consumption. In Proceedings of the 18th annual international conference on Mobile computing and networking, Mobicom '12, pages 317--328, New York, NY, USA, 2012. ACM.

Digital Library

[22]

A. Noureddine, R. Rouvoy, and L. Seinturier. A review of energy measurement approaches. SIGOPS Operating Systems Review, 47(3):42--49, Nov. 2013.

Digital Library

[23]

A. Noureddine, R. Rouvoy, and L. Seinturier. Unit testing of energy consumption of software libraries. In Proceedings of the 29th Annual ACM Symposium on Applied Computing, SAC '14, pages 1200--1205, New York, NY, USA, 2014. ACM.

Digital Library

[24]

A. Noureddine, R. Rouvoy, and L. Seinturier. Monitoring energy hotspots in software. Automated Software Engineering, pages 1--42, 2015.

Digital Library

[25]

A. Pathak, Y. C. Hu, and M. Zhang. Where is the energy spent inside my app?: fine grained energy accounting on smartphones with eprof. In Proceedings of the 7th ACM european conf. on Computer Systems, EuroSys '12, pages 29--42, New York, NY, USA, 2012. ACM.

Digital Library

[26]

G. Pinto, F. Castor, and Y. D. Liu. Mining questions about software energy consumption. In Proceedings of the 11th Working Conference on Mining Software Repositories, MSR 2014, pages 22--31, New York, NY, USA, 2014. ACM.

Digital Library

[27]

G. Pinto, F. Castor, and Y. D. Liu. Understanding energy behaviors of thread management constructs. SIGPLAN Not., 49(10):345--360, Oct. 2014.

Digital Library

[28]

G. Procaccianti, P. Lago, and G. A. Lewis. A catalogue of green architectural tactics for the cloud. In Maint. and Evol. of Service-Oriented and Cloud-Based Systems (MESOCA), 2014 IEEE 8th Int'l Symp. on the, pages 29--36, Sept 2014.

Digital Library

[29]

G. Procaccianti, P. Lago, A. Vetro, D. M. Fernández, and R. Wieringa. The green lab: Experimentation in software energy efficiency. In Proceedings of the 37th International Conference on Software Engineering (ICSE), 2015.

Digital Library

[30]

N. Rozanski and E. Woods. Software systems architecture: working with stakeholders using viewpoints and perspectives. Addison-Wesley, 2012.

Digital Library

[31]

P. Runeson and M. Höst. Guidelines for conducting and reporting case study research in software engineering. Empirical software engineering, 14(2):131--164, 2009.

Digital Library

[32]

W. Shang, Z. M. Jiang, B. Adams, A. E. Hassan, M. W. Godfrey, M. Nasser, and P. Flora. An exploratory study of the evolution of communicated information about the execution of large software systems. Journal of Software: Evolution and Process, 26(1):3--26, 2014.

[33]

Y. Sun, Y. Zhao, Y. Song, Y. Yang, H. Fang, H. Zang, Y. Li, and Y. Gao. Green challenges to system software in data centers. Frontiers of Comp. Sc. in China, 5(3):353--368, 2011.

Digital Library

[34]

R. Tibshirani. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. Series B Stat. Methodol., 58(1):267--288, 1 Jan. 1996.

[35]

A. E. Trefethen and J. Thiyagalingam. Energy-aware software: Challenges, opportunities and strategies. Journal of Computational Science, 4(6):444--449, 2013. Scalable Algorithms for Large-Scale Systems Workshop (ScalA2011), Supercomputing 2011.

[36]

C. Wohlin, P. Runeson, M. Hst, M. C. Ohlsson, B. Regnell, and A. Wessln. Experimentation in Software Engineering. Springer Publishing Company, Incorporated, 2012.

[37]

L. Xu and S. Brinkkemper. Concepts of product software. European Journal of Information Systems, 16(5):531--541, 2007.

[38]

G. Zhang, K. Zhang, X. Zhu, M. Chen, C. Xu, and Y. Shao. Modeling and analyzing method for cps software architecture energy consumption. Journal of Software, 8(11), 2013.

[39]

H. Zhu, C. Lin, and Y. Liu. A programming model for sustainable software. In Software Engineering (ICSE), 2015 IEEE/ACM 37th IEEE International Conference on, volume 1, pages 767--777, May 2015.

Digital Library

Cited By

Lopez Londoño BAzizi SFinnveden G(2024)Incorporation of software in the life cycle assessment of an ICT service: A case study of an ICT service for energy efficiency in the transport sectorJournal of Industrial Ecology10.1111/jiec.1357028:6(1965-1978)Online publication date: 12-Nov-2024
https://doi.org/10.1111/jiec.13570
Lee SFernando NLee KSchneider J(2024)A survey of energy concerns for software engineeringJournal of Systems and Software10.1016/j.jss.2023.111944210(111944)Online publication date: Apr-2024
https://doi.org/10.1016/j.jss.2023.111944
Wedyan FMorrison RAbuomar O(2023)Integration and Unit Testing of Software Energy Consumption2023 Tenth International Conference on Software Defined Systems (SDS)10.1109/SDS59856.2023.10329262(60-64)Online publication date: 23-Oct-2023
https://doi.org/10.1109/SDS59856.2023.10329262
Show More Cited By

Index Terms

Software energy profiling: comparing releases of a software product
1. General and reference
  1. Cross-computing tools and techniques
    1. Metrics

Recommendations

Software Development Lifecycle for Energy Efficiency: Techniques and Tools

Motivation: In modern it systems, the increasing demand for computational power is tightly coupled with ever higher energy consumption. Traditionally, energy efficiency research has focused on reducing energy consumption at the hardware level. ...
Energy profiling using IgProf
CCGRID '15: Proceedings of the 15th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing

Energy efficiency has become a primary concern for data centers in recent years. Understanding where the energy has been spent within a software is fundamental for energy-efficiency study as a whole. In this paper, we take the first step towards this ...
Empirical evaluation of two best practices for energy-efficient software development

We empirically studied the energy impact of two best practices for energy-efficient software.We applied the practices on two widely used software applications, MySQL Server and Apache Webserver.Each practice successfully reduced the energy consumption ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

ICSE '16: Proceedings of the 38th International Conference on Software Engineering Companion

May 2016

946 pages

ISBN:9781450342056

DOI:10.1145/2889160

General Chair:
Laura Dillon
Michigan State University
,
Program Chairs:
Willem Visser
Stellenbosch University, South Africa
,
Laurie Williams
North Carolina State University

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
IEEE-CS\TCSE: TC on Software Engineering
IEEE-CS\DATC: IEEE Computer Society

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 May 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

ICSE '16

Sponsor:

ACM
SIGSOFT
IEEE-CS\TCSE
IEEE-CS\DATC

ICSE '16: 38th International Conference on Software Engineering

May 14 - 22, 2016

Texas, Austin

Acceptance Rates

Overall Acceptance Rate 276 of 1,856 submissions, 15%

Upcoming Conference

ICSE 2025

2025 IEEE/ACM 46th International Conference on Software Engineering

April 26 - May 3, 2025

Ottawa , ON , Canada

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

20
Total Citations
View Citations
424
Total Downloads

Downloads (Last 12 months)37
Downloads (Last 6 weeks)2

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Lopez Londoño BAzizi SFinnveden G(2024)Incorporation of software in the life cycle assessment of an ICT service: A case study of an ICT service for energy efficiency in the transport sectorJournal of Industrial Ecology10.1111/jiec.1357028:6(1965-1978)Online publication date: 12-Nov-2024
https://doi.org/10.1111/jiec.13570
Lee SFernando NLee KSchneider J(2024)A survey of energy concerns for software engineeringJournal of Systems and Software10.1016/j.jss.2023.111944210(111944)Online publication date: Apr-2024
https://doi.org/10.1016/j.jss.2023.111944
Wedyan FMorrison RAbuomar O(2023)Integration and Unit Testing of Software Energy Consumption2023 Tenth International Conference on Software Defined Systems (SDS)10.1109/SDS59856.2023.10329262(60-64)Online publication date: 23-Oct-2023
https://doi.org/10.1109/SDS59856.2023.10329262
Simon TRust PRouvoy RPenhoat J(2023)Uncovering the Environmental Impact of Software Life Cycle2023 International Conference on ICT for Sustainability (ICT4S)10.1109/ICT4S58814.2023.00026(176-187)Online publication date: 5-Jun-2023
https://doi.org/10.1109/ICT4S58814.2023.00026
España Svan der Maaten CGulden JPastor Ó(2023)A Survey of Ethical Reasoning Methods, Their Metamodels, and a Discussion on Their Application to Conceptual ModellingConceptual Modeling10.1007/978-3-031-47262-6_2(23-44)Online publication date: 29-Oct-2023
https://doi.org/10.1007/978-3-031-47262-6_2
Guégain ÉQuinton CRouvoy RMousavi MSchobbens P(2021)On reducing the energy consumption of software product linesProceedings of the 25th ACM International Systems and Software Product Line Conference - Volume A10.1145/3461001.3471142(89-99)Online publication date: 6-Sep-2021
https://dl.acm.org/doi/10.1145/3461001.3471142
Mancebo JCalero CGarcia FMoraga MGarcia-Rodriguez de Guzman I(2021)FEETINGS: Framework for Energy Efficiency Testing to Improve Environmental Goal of the SoftwareSustainable Computing: Informatics and Systems10.1016/j.suscom.2021.10055830(100558)Online publication date: Jun-2021
https://doi.org/10.1016/j.suscom.2021.100558
Mancebo JCalero CGarcía F(2021)Does maintainability relate to the energy consumption of software? A case studySoftware Quality Journal10.1007/s11219-020-09536-9Online publication date: 6-Jan-2021
https://doi.org/10.1007/s11219-020-09536-9
Mancebo JCalero CGarcía F(2021)GSMP: Green Software Measurement ProcessSoftware Sustainability10.1007/978-3-030-69970-3_3(43-67)Online publication date: 6-Oct-2021
https://doi.org/10.1007/978-3-030-69970-3_3
Guldner AKern EKreten SNaumann S(2021)Criteria for Sustainable Software Products: Analyzing Software, Informing Users, and PoliticsSoftware Sustainability10.1007/978-3-030-69970-3_2(17-42)Online publication date: 6-Oct-2021
https://doi.org/10.1007/978-3-030-69970-3_2
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten