Generative programming: methods, tools, and applications
Generative programming: methods, tools, and applications
Reasoning about edits to feature models
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Viewpoint-Oriented Variability Modeling
COMPSAC '09 Proceedings of the 2009 33rd Annual IEEE International Computer Software and Applications Conference - Volume 01
Automated analysis of feature models 20 years later: A literature review
Information Systems
Multi-dimensional variability modeling
Proceedings of the 5th Workshop on Variability Modeling of Software-Intensive Systems
Aspect-oriented feature models
MODELS'10 Proceedings of the 2010 international conference on Models in software engineering
Configuration coverage in the analysis of large-scale system software
PLOS '11 Proceedings of the 6th Workshop on Programming Languages and Operating Systems
Abstract Features in Feature Modeling
SPLC '11 Proceedings of the 2011 15th International Software Product Line Conference
SLE'09 Proceedings of the Second international conference on Software Language Engineering
Feature models, grammars, and propositional formulas
SPLC'05 Proceedings of the 9th international conference on Software Product Lines
Multi-perspectives on feature models
MODELS'12 Proceedings of the 15th international conference on Model Driven Engineering Languages and Systems
Towards modular analysis of multi product lines
Proceedings of the 17th International Software Product Line Conference co-located workshops
The feature pack approach: systematically managing implementations in software ecosystems
Proceedings of the Eighth International Workshop on Variability Modelling of Software-Intensive Systems
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Feature models specify valid combinations of features in software product lines. With dependent feature models (DFMs), we apply separation of concerns to feature models for two main benefits. First, we can modularize feature models into parts relevant to groups of stakeholders. Second, we are able to model dependencies between different software product lines in a multi-product-line scenario. To ensure consistency and correctness of DFMs, we have to apply analyses, such as dead-feature detection. We discuss why DFMs challenge the detection of inconsistencies, present how to reuse existing analyses for DFMs, and propose new analyses to supplement existing ones. We apply automated analyses in five steps and evaluate the approach using DFMs specified in VELVET by our prototype VeAnalyzer.