research-article

Implicit constraints in partial feature models

Authors:

Sofia Ananieva,

Matthias Kowal,

Ina SchaeferAuthors Info & Claims

FOSD 2016: Proceedings of the 7th International Workshop on Feature-Oriented Software Development

Pages 18 - 27

https://doi.org/10.1145/3001867.3001870

Published: 30 October 2016 Publication History

Abstract

Developing and maintaining a feature model is a tedious process and gets increasingly difficult with regard to large product lines consisting of thousands of features and constraints. In addition, these large-scale feature models typically involve several stakeholders from different domains during development and maintenance. We aim at supporting such stakeholders by deriving and explaining implicit constraints for partial feature models. A partial feature model can either be a submodel of a feature model representing the full product line or a specific feature model in a set of interrelated models. For every implicit constraint, we generate an explanation exposing which other model parts and constraints interfere with the partial model of interest. Thus, stakeholders are only confronted with a small part of the feature model reducing the complexity while preserving the necessary information about dependencies. Our approach is implemented in the open-source framework FeatureIDE.

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Cited By

Meixner KFeichtinger KGreiner SRabiser R(2024)On Configuration Sequences in Feature ModelsProceedings of the 18th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3634713.3634730(146-148)Online publication date: 7-Feb-2024
https://dl.acm.org/doi/10.1145/3634713.3634730
Meixner KFeichtinger KFadhlillah HGreiner SMarcher HRabiser RBiffl S(2024)Variability modeling of products, processes, and resources in cyber–physical production systems engineeringJournal of Systems and Software10.1016/j.jss.2024.112007211(112007)Online publication date: May-2024
https://doi.org/10.1016/j.jss.2024.112007
Stötzner MKlinaku FPesl RBecker SFu SCarnevale LRana OVillari M(2023)Enhancing Deployment Variability Management by Pruning Elements in Deployment ModelsProceedings of the IEEE/ACM 16th International Conference on Utility and Cloud Computing10.1145/3603166.3632143(1-11)Online publication date: 4-Dec-2023
https://dl.acm.org/doi/10.1145/3603166.3632143
Show More Cited By

Index Terms

Implicit constraints in partial feature models
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. Project and people management
2. Software and its engineering
  1. Software creation and management
    1. Software development process management
    2. Software development techniques
      1. Reusability
  2. Software notations and tools
    1. Software configuration management and version control systems
    2. Software libraries and repositories

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cover image ACM Conferences

FOSD 2016: Proceedings of the 7th International Workshop on Feature-Oriented Software Development

October 2016

84 pages

ISBN:9781450346474

DOI:10.1145/3001867

General Chairs:
Christoph Seidl,
Leopoldo Teixeira

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]

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Published: 30 October 2016

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SPLASH '16: Conference on Systems, Programming, Languages, and Applications: Software for Humanity

October 30, 2016

Amsterdam, Netherlands

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Cited By

Meixner KFeichtinger KGreiner SRabiser R(2024)On Configuration Sequences in Feature ModelsProceedings of the 18th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3634713.3634730(146-148)Online publication date: 7-Feb-2024
https://dl.acm.org/doi/10.1145/3634713.3634730
Meixner KFeichtinger KFadhlillah HGreiner SMarcher HRabiser RBiffl S(2024)Variability modeling of products, processes, and resources in cyber–physical production systems engineeringJournal of Systems and Software10.1016/j.jss.2024.112007211(112007)Online publication date: May-2024
https://doi.org/10.1016/j.jss.2024.112007
Stötzner MKlinaku FPesl RBecker SFu SCarnevale LRana OVillari M(2023)Enhancing Deployment Variability Management by Pruning Elements in Deployment ModelsProceedings of the IEEE/ACM 16th International Conference on Utility and Cloud Computing10.1145/3603166.3632143(1-11)Online publication date: 4-Dec-2023
https://dl.acm.org/doi/10.1145/3603166.3632143
Sundermann CHeß TNieke MBittner PYoung JThüm TSchaefer I(2023)Evaluating state-of-the-art # SAT solvers on industrial configuration spacesEmpirical Software Engineering10.1007/s10664-022-10265-928:2Online publication date: 13-Jan-2023
https://dl.acm.org/doi/10.1007/s10664-022-10265-9
Young JBittner PWalkingshaw EThüm T(2023)Variational satisfiability solving: efficiently solving lots of related SAT problemsEmpirical Software Engineering10.1007/s10664-022-10217-328:1Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1007/s10664-022-10217-3
Vidal-Silva CDuarte VCardenas-Cobo JSerrano-Malebran JVeas IRubio-León J(2022)Reviewing Automated Analysis of Feature Model Solutions for the Product ConfigurationApplied Sciences10.3390/app1301017413:1(174)Online publication date: 23-Dec-2022
https://doi.org/10.3390/app13010174
Hentze MPett TSundermann CKrieter SThüm TSchaefer IScholz BKameyama Y(2022)Generic Solution-Space Sampling for Multi-domain Product LinesProceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences10.1145/3564719.3568695(135-147)Online publication date: 29-Nov-2022
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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
Kahraman GCleophas LFelfernig AFuentes L(2022)A tool for modeling and analysis of relationships among feature model viewsProceedings of the 26th ACM International Systems and Software Product Line Conference - Volume B10.1145/3503229.3547076(103-109)Online publication date: 12-Sep-2022
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Kahraman GCleophas LSchiffelers R(2021)Modeling Relationships Between Feature Model Views2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)10.1109/MODELS-C53483.2021.00067(437-446)Online publication date: Oct-2021
https://doi.org/10.1109/MODELS-C53483.2021.00067
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