Global Constraints on Feature Models

KARATAS, Ahmet Serkan
Doğru, Ali Hikmet
Feature modeling has been found very effective for modeling and managing variability in Software Product Lines. The nature of feature models invites, sometimes even requires, the use of global constraints. This paper lays the groundwork for the inclusion of global constraints in automated reasoning on feature models. We present a mapping from extended feature models to constraint logic programming over finite domains, and show that this mapping enables using global constraints on feature attributes, as well as features, for a variety of analysis operations on feature models. We also present performance test results and discuss the benefits of using global constraints.


FMML: A Feature Model Markup Language
NABDEL, Leili; Karatas, Ahmet Serkan; Oğuztüzün, Mehmet Halit S.; Dogru, Ali (2011-09-25)
Feature modeling is a common way of representing commonality and variability in Software Product Line Engineering. Alternative notations are available to represent feature models. Compared with graphical notations, text-based notations can be more amenable to automated processing and tool interoperability. In this paper, we propose an XML-based feature modeling language to represent extended feature models with complex relationships.
Multi–target implementation of a domain specific language for extended feature models
Demirtaş, Görkem; Oğuztüzün, Mehmet Halit S.; Department of Computer Engineering (2018)
Translation of feature models to constraint logic programs is an effective method to enable their automated analysis using existing constraint solvers. More flexibility can be offered for building and application of analysis operations on extended feature models by providing a syntax and mechanism for interfacing the host solver with user defined constraint predicates. These constraints, such as global constraints, can be provided by the constraint solver runtime or by the translator itself as a part of the...
Feature modeling and automated analysis for an embedded software product family
Fedakar Gönül, Gülseren; Oğuztüzün, Mehmet Halit S.; Department of Computer Engineering (2013)
In the context of software product line engineering, feature models are used for modeling variability and commonality in product families. This thesis presents a basic feature model for a commercial television set product family. This work consists of three stages. First, a feature model is constructed, based on the analysis of the product family requirements. The constructed model is supplemented with a feature glossary. FeatureIDE is used as the model editor. Feature attributes, not supported by FeatureID...
Comparison of regression techniques via Monte Carlo simulation
Mutan, Oya Can; Ayhan, Hüseyin Öztaş; Department of Statistics (2004)
The ordinary least squares (OLS) is one of the most widely used methods for modelling the functional relationship between variables. However, this estimation procedure counts on some assumptions and the violation of these assumptions may lead to nonrobust estimates. In this study, the simple linear regression model is investigated for conditions in which the distribution of the error terms is Generalised Logistic. Some robust and nonparametric methods such as modified maximum likelihood (MML), least absolut...
From extended feature models to constraint logic programming
KARATAS, Ahmet Serkan; Oğuztüzün, Mehmet Halit S.; Dogru, Ali (2013-12-01)
Since feature models for realistic product families may be quite complicated, the automated analysis of feature models is desirable. Although several approaches reported in the literature address this issue, complex cross-tree relationships involving attributes in extended feature models have not been handled. In this article, we introduce a mapping from extended feature models to constraint logic programming over finite domains. This mapping is used to translate into constraint logic programs; basic, cardi...
Citation Formats
A. S. KARATAS, H. OGUZTUZUN, and A. H. Doğru, “Global Constraints on Feature Models,” 2010, vol. 6308, Accessed: 00, 2020. [Online]. Available: