short-paper

Trace checking for dynamic software product lines

Authors:

Rafael Olaechea,

Uli FahrenbergAuthors Info & Claims

SEAMS '18: Proceedings of the 13th International Conference on Software Engineering for Adaptive and Self-Managing Systems

Pages 69 - 75

https://doi.org/10.1145/3194133.3194143

Published: 28 May 2018 Publication History

Abstract

A key objective of self-adaptive systems is to continue to provide optimal quality of service when the environment changes. A dynamic software product line (DSPL) can benefit from knowing how its various product variants would have performed (in terms of quality of service) with respect to the recent history of inputs. We propose a family-based analysis that simulates all the product variants of a DSPL simultaneously, at runtime, on recent environmental inputs to obtain an estimate of the quality of service that each one of the product variants would have had, provided it had been executing. We assessed the efficiency of our DSPL analysis compared to the efficiency of analyzing each product individually on three case studies. We obtained mixed results due to the explosion of quality-of-service values for the product variants of a DSPL. After introducing a simple data abstraction on the values of quality-of- service variables, our DSPL analysis is between 1.4 and 7.7 times faster than analyzing the products one at a time.

References

[1]

C. Baier and J.-P. Katoen. Principles of Model Checking. The MIT Press, 2008.

Digital Library

[2]

R. Calinescu, L. Grunske, M. Kwiatkowska, R. Mirandola, and G. Tamburrelli. Dynamic qos management and optimization in service-based systems. IEEE Trans. Softw. Eng., 37(3):387--409, 2011.

Digital Library

[3]

J. Camara, A. Lopes, D. Garlan, and B. R. Schmerl. Impact models for architecture-based self-adaptive systems. In Proceedings of the 11th International Symposium on Formal Aspects of Component Software, FACS '14, 2014.

[4]

S.-W. Cheng and D. Garlan. Stitch: A language for architecture-based self-adaptation. J. Syst. Softw., 85(12):2860--2875, Dec. 2012.

Digital Library

[5]

A. Classen, P. Heymans, P.-Y. Schobbens, and A. Legay. Symbolic model checking of software product lines. In Proceedings of the 33rd International Conference on Software Engineering, ICSE '11, 2011.

Digital Library

[6]

A. Classen, M. Cordy, P.-Y. Schobbens, P. Heymans, A. Legay, and J.-F. Raskin. Featured transition systems: Foundations for verifying variability-intensive systems and their application to LTL model checking. IEEE Trans. Softw. Eng., 39(8): 1069--1089, Aug. 2013.

Digital Library

[7]

M. Cordy, A. Classen, P. Heymans, P.-Y. Schobbens, and A. Legay. Provelines: A product line of verifiers for software product lines. In Proceedings of the 17th International Software Product Line Conference, SPLC '13, 2013.

Digital Library

[8]

M. Felder and A. Morzenti. Validating real-time systems by history-checking trio specifications. In Proceedings of the 14th International Conference on Software Engineering, ICSE '92, 1992.

Digital Library

[9]

A. Filieri, C. Ghezzi, and G. Tamburrelli. Run-time efficient probabilistic model checking. In Proceedings of the 33rd International Conference on Software Engineering, ICSE '11, 2011.

Digital Library

[10]

A. Filieri, G. Tamburrelli, and C. Ghezzi. Supporting self-adaptation via quantitative verification and sensitivity analysis at run time. IEEE Transactions on Software Engineering, 42(1):75--99, Jan 2016.

Digital Library

[11]

B. Finkbeiner, S. Sankaranarayanan, and H. B. Sipma. Collecting statistics over runtime executions. Form. Methods Syst. Des., 27(3):253--274, Nov. 2005.

Digital Library

[12]

S. Gerasimou, R. Calinescu, and A. Banks. Efficient runtime quantitative verification using caching, lookahead, and nearly-optimal reconfiguration. In Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS '09, 2014.

Digital Library

[13]

C. Ghezzi and A. M. Sharifloo. Dealing with non-functional requirements for adaptive systems via dynamic software product-lines. In Software Engineering for Self-Adaptive Systems II - International Seminar, Dagstuhl Castle, Germany, October 24--29, 2010., 2010.

[14]

C. Ghezzi, L. S. Pinto, P. Spoletini, and G. Tamburrelli. Managing non-functional uncertainty via model-driven adaptivity. In Proceedings of the 2013 International Conference on Software Engineering, ICSE '13, 2013.

Digital Library

[15]

S. Hallsteinsen, E. Stav, A. Solberg, and J. Floch. Using product line techniques to build adaptive systems. In Proceedings ofthe 10th International on Software Product Line Conference, SPLC '06, 2006.

Digital Library

[16]

K. C. Kang, S. G. Cohen, J. A. Hess, W. E. Novak, and A. S. Peterson. Feature-Oriented Domain Analysis feasibility study. Technical report, SEI-CMU, 1990.

[17]

M. Kwiatkowska, G. Norman, and D. Parker. Prism: Probabilistic model checking for performance and reliability analysis. SIGMETRICS Perform. Eval. Rev., 36(4): 40--45, Mar. 2009.

Digital Library

[18]

G. A. Moreno, J. Camara, D. Garlan, and B. Schmerl. Proactive self-adaptation under uncertainty: A probabilistic model checking approach. In Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, ESEC/FSE 2015, 2015.

Digital Library

[19]

G. A. Moreno, J. Camara, D. Garlan, and B. R. Schmerl. Efficient decision-making under uncertainty for proactive self-adaptation. In Proceedings of the 13th International Conference on Autonomic Computing, ICAC '16, 2016.

[20]

G. A. Moreno, O. Strichman, S. Chaki, and R. Vaisman. Decision-making with cross-entropy for self-adaptation. In Proceedings of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS '13, 2017.

Digital Library

[21]

G. G. Pascual, M. Pinto, and L. Fuentes. Run-time adaptation of mobile applications using genetic algorithms. In Proceedings of the 8th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS '13, 2013.

Digital Library

[22]

G. G. Pascual, R. E. Lopez-Herrejon, M. Pinto, L. Fuentes, and A. Egyed. Applying multiobjective evolutionary algorithms to dynamic software product lines for reconfiguring mobile applications. J. Syst. Softw., 103(C):392--411, May 2015.

Digital Library

[23]

M. Plath and M. Ryan. Feature integration using a feature construct. Sci. Comput. Program., 41(1):53--84, Sept. 2001.

Digital Library

[24]

M. H. ter Beek, A. Legay, A. L. Lafuente, and A. Vandin. Statistical analysis of probabilistic models of software product lines with quantitative constraints. In Proceedings of the 19th International Conference on Software Product Line, SPLC '15, 2015.

Digital Library

[25]

D. Weyns and R. Calinescu. Tele assistance: A self-adaptive service-based system examplar. In Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS '15, 2015.

Digital Library

Cited By

Aguayo OSepúlveda S(2022)Variability Management in Dynamic Software Product Lines for Self-Adaptive Systems—A Systematic MappingApplied Sciences10.3390/app12201024012:20(10240)Online publication date: 12-Oct-2022
https://doi.org/10.3390/app122010240
Lazreg SBohlachov VRana LHein ACordy M(2022)Variability-Aware Design of Space Systems: Variability Modelling, Configuration Workflow and Research DirectionsProceedings of the 16th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3510466.3510472(1-10)Online publication date: 23-Feb-2022
https://dl.acm.org/doi/10.1145/3510466.3510472
García SStrüber DBrugali DDi Fava APelliccione PBerger T(2022)Software variability in service roboticsEmpirical Software Engineering10.1007/s10664-022-10231-528:2Online publication date: 24-Dec-2022
https://dl.acm.org/doi/10.1007/s10664-022-10231-5
Show More Cited By

Recommendations

Model checking software product lines with SNIP

We present SNIP, an efficient model checker for software product lines (SPLs). Variability in software product lines is generally expressed in terms of features, and the number of potential products is exponential in the number of features. Whereas ...
Delta-oriented multi software product lines
SPLC '14: Proceedings of the 18th International Software Product Line Conference - Volume 1

Modern software systems outgrow the scope of traditional software product lines (SPLs) resulting in multi software product lines (MSPLs) with many interconnected subsystem versions and variants. Delta-oriented programming (DOP) is a flexible, modular ...
A Production System for Software Product Lines
SPLC '07: Proceedings of the 11th International Software Product Line Conference

Companies such as Toyota have achieved significant competitive advantage by treating product production as a system that can be planned and optimized. Software product line organizations can achieve similar advantage when they explicitly coordinate the ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SEAMS '18: Proceedings of the 13th International Conference on Software Engineering for Adaptive and Self-Managing Systems

May 2018

244 pages

ISBN:9781450357159

DOI:10.1145/3194133

General Chair:
Jesper Andersson
Linnaeus University, Sweden
,
Program Chair:
Danny Weyns
Katholieke Universiteit Leuven, Belgium | Linnaeus University, Sweden

Copyright © 2018 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 the author(s) 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

SIGSOFT: ACM Special Interest Group on Software Engineering
IEEE-CS: Computer Society

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 May 2018

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Short-paper

Conference

ICSE '18

Sponsor:

SIGSOFT
IEEE-CS

ICSE '18: 40th International Conference on Software Engineering

May 28 - 29, 2018

Gothenburg, Sweden

Acceptance Rates

Overall Acceptance Rate 17 of 31 submissions, 55%

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

7
Total Citations
View Citations
146
Total Downloads

Downloads (Last 12 months)7
Downloads (Last 6 weeks)1

Reflects downloads up to 18 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Aguayo OSepúlveda S(2022)Variability Management in Dynamic Software Product Lines for Self-Adaptive Systems—A Systematic MappingApplied Sciences10.3390/app12201024012:20(10240)Online publication date: 12-Oct-2022
https://doi.org/10.3390/app122010240
Lazreg SBohlachov VRana LHein ACordy M(2022)Variability-Aware Design of Space Systems: Variability Modelling, Configuration Workflow and Research DirectionsProceedings of the 16th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3510466.3510472(1-10)Online publication date: 23-Feb-2022
https://dl.acm.org/doi/10.1145/3510466.3510472
García SStrüber DBrugali DDi Fava APelliccione PBerger T(2022)Software variability in service roboticsEmpirical Software Engineering10.1007/s10664-022-10231-528:2Online publication date: 24-Dec-2022
https://dl.acm.org/doi/10.1007/s10664-022-10231-5
Cordy MDevroey XLegay APerrouin GClassen AHeymans PSchobbens PRaskin J(2022)A Decade of Featured Transition SystemsFrom Software Engineering to Formal Methods and Tools, and Back10.1007/978-3-030-30985-5_18(285-312)Online publication date: 11-Mar-2022
https://dl.acm.org/doi/10.1007/978-3-030-30985-5_18
Bezerra CLima RSilva P(2021)DyMMer 2.0: A Tool for Dynamic Modeling and Evaluation of Feature ModelProceedings of the XXXV Brazilian Symposium on Software Engineering10.1145/3474624.3476016(121-126)Online publication date: 27-Sep-2021
https://dl.acm.org/doi/10.1145/3474624.3476016
Annighoefer BReinhart JBrunner MSchulz B(2021)The Concept of an Autonomic Avionics Platform and the Resulting Software Engineering Challenges2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)10.1109/SEAMS51251.2021.00031(179-185)Online publication date: May-2021
https://doi.org/10.1109/SEAMS51251.2021.00031
Gadelha RVieira LMonteiro DVidal FMaia P(2020)Scen@rist: an approach for verifying self-adaptive systems using runtime scenariosSoftware Quality Journal10.1007/s11219-019-09486-x28:3(1303-1345)Online publication date: 1-Sep-2020
https://dl.acm.org/doi/10.1007/s11219-019-09486-x
Lazreg SCordy MCollet PHeymans PMosser SAtlee JBultan TWhittle J(2019)Multifaceted automated analyses for variability-intensive embedded systemsProceedings of the 41st International Conference on Software Engineering10.1109/ICSE.2019.00092(854-865)Online publication date: 25-May-2019
https://dl.acm.org/doi/10.1109/ICSE.2019.00092

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