research-article

Symbolic model checking of software product lines

Authors:

Andreas Classen,

Patrick Heymans,

Pierre-Yves Schobbens,

Axel LegayAuthors Info & Claims

ICSE '11: Proceedings of the 33rd International Conference on Software Engineering

Pages 321 - 330

https://doi.org/10.1145/1985793.1985838

Published: 21 May 2011 Publication History

Abstract

We study the problem of model checking software product line (SPL) behaviours against temporal properties. This is more difficult than for single systems because an SPL with n features yields up to 2ⁿ individual systems to verify. As each individual verification suffers from state explosion, it is crucial to propose efficient formalisms and heuristics.

We recently proposed featured transition systems (FTS), a compact representation for SPL behaviour, and defined algorithms for model checking FTS against linear temporal properties. Although they showed to outperform individual system verifications, they still face a state explosion problem as they enumerate and visit system states one by one.

In this paper, we tackle this latter problem by using symbolic representations of the state space. This lead us to consider computation tree logic (CTL) which is supported by the industry-strength symbolic model checker NuSMV. We first lay the foundations for symbolic SPL model checking by defining a feature-oriented version of CTL and its dedicated algorithms. We then describe an implementation that adapts the NuSMV language and tool infrastructure. Finally, we propose theoretical and empirical evaluations of our results. The benchmarks show that for certain properties, our algorithm is over a hundred times faster than model checking each system with the standard algorithm.

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Cited By

Comet JCollavizza HGibart L(2024)Constrained Kripke Structure for Identifying Parameters of Biological ModelsTheoretical Computer Science10.1016/j.tcs.2024.114505(114505)Online publication date: Mar-2024
https://doi.org/10.1016/j.tcs.2024.114505
Casaluce RBurattin AChiaromonte FLafuente AVandin A(2024)White-box validation of quantitative product lines by statistical model checking and process miningJournal of Systems and Software10.1016/j.jss.2024.111983210:COnline publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1016/j.jss.2024.111983
Rousseaux TCrochet CAoga JLegay A(2024)Network Simulator-Centric Compositional TestingFormal Techniques for Distributed Objects, Components, and Systems10.1007/978-3-031-62645-6_10(177-196)Online publication date: 13-Jun-2024
https://doi.org/10.1007/978-3-031-62645-6_10
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Index Terms

Symbolic model checking of software product lines
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Formal software verification
  2. Software organization and properties
    1. Software functional properties
      1. Formal methods
        Model checking
2. Theory of computation
  1. Logic
    1. Verification by model checking

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Published In

cover image ACM Conferences

ICSE '11: Proceedings of the 33rd International Conference on Software Engineering

May 2011

1258 pages

ISBN:9781450304450

DOI:10.1145/1985793

General Chair:
Richard N. Taylor
UC Irvine, USA
,
Program Chairs:
Harald Gall
University of Zurich, Switzerland
,
Nenad Medvidović
University of Southern California, USA

Copyright © 2011 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]

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Publication History

Published: 21 May 2011

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ICSE11: International Conference on Software Engineering

May 21 - 28, 2011

HI, Waikiki, Honolulu, USA

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

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Cited By

Comet JCollavizza HGibart L(2024)Constrained Kripke Structure for Identifying Parameters of Biological ModelsTheoretical Computer Science10.1016/j.tcs.2024.114505(114505)Online publication date: Mar-2024
https://doi.org/10.1016/j.tcs.2024.114505
Casaluce RBurattin AChiaromonte FLafuente AVandin A(2024)White-box validation of quantitative product lines by statistical model checking and process miningJournal of Systems and Software10.1016/j.jss.2024.111983210:COnline publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1016/j.jss.2024.111983
Rousseaux TCrochet CAoga JLegay A(2024)Network Simulator-Centric Compositional TestingFormal Techniques for Distributed Objects, Components, and Systems10.1007/978-3-031-62645-6_10(177-196)Online publication date: 13-Jun-2024
https://doi.org/10.1007/978-3-031-62645-6_10
ÖZTÜRK KAYA DTUĞLULAR T(2023)Yazılım Ürün Hatlarında Tam Üründen Özellik Eksiltme Yoluyla Farklı Ürün Yapılandırmalarını Otomatik Üretme YöntemiThe software product line (SPL) is a promising approach to developing software systems that are complex, large-scale, and rich in product configuration. The automatic acquisition of product configurations’ models, which may be too many in the software product line, is very important in terms of time and cost constraints. In this study, we propose an approach that automatically extracts models of different product configurations from the full product model by feature deduction to obtain product models more productively and effectively. We validated the proposed approach on three different case studies: Soda Vending Machine SPL, Bank Account SPL, and Student Attendance System SPL. The two novelties of this study are the feature-dependency tree and the dynamic edge mapping algorithm.Deu Muhendislik Fakultesi Fen ve Muhendislik10.21205/deufmd.202325731825:73(217-238)Online publication date: 26-Jan-2023
https://doi.org/10.21205/deufmd.2023257318
Kaya DTuglular TBelli F(2023)Software Product Line Testing based on Event Sequence Graphs with Feature Expressions2023 8th International Conference on Computer Science and Engineering (UBMK)10.1109/UBMK59864.2023.10286660(175-180)Online publication date: 13-Sep-2023
https://doi.org/10.1109/UBMK59864.2023.10286660
Hentze MSundermann CThüm TSchaefer ISyriani ESahraoui H(2022)Quantifying the variability mismatch between problem and solution spaceProceedings of the 25th International Conference on Model Driven Engineering Languages and Systems10.1145/3550355.3552411(322-333)Online publication date: 23-Oct-2022
https://dl.acm.org/doi/10.1145/3550355.3552411
Lazreg SCordy MLegay A(2022)Verification of Variability-Intensive Stochastic Systems with Statistical Model CheckingLeveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning10.1007/978-3-031-19759-8_27(448-471)Online publication date: 22-Oct-2022
https://dl.acm.org/doi/10.1007/978-3-031-19759-8_27
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
Santos EMousavi MSchobbens P(2021)STARSProceedings of the 25th ACM International Systems and Software Product Line Conference - Volume B10.1145/3461002.3473068(13-17)Online publication date: 6-Sep-2021
https://dl.acm.org/doi/10.1145/3461002.3473068
Aoyama YKuroiwa TKushiro N(2021)Executable Test Case Generation from Specifications Written in Natural Language and Test Execution Environment2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC)10.1109/CCNC49032.2021.9369549(1-6)Online publication date: 9-Jan-2021
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