FMML: A Feature Model Markup Language

Date

2011-09-25

Author

NABDEL, Leili
Karatas, Ahmet Serkan
Oğuztüzün, Mehmet Halit S.
Dogru, Ali

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

214
views

0
downloads

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.

Subject Keywords

Feature model markup language, Extended feature model, Complex constraint

URI

https://hdl.handle.net/11511/47501

DOI

https://doi.org/10.1063/1.3636864

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Global Constraints on Feature Models KARATAS, Ahmet Serkan; OGUZTUZUN, Halit; Doğru, Ali Hikmet (2010-09-10) 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...
An xml-based feature modeling language Nabdel, Leili; Oğuztüzün, Mehmet Halit S.; Karataş, Ahmet Serkan; Department of Computer Engineering (2011) Feature modeling is a common way of representing commonality and variability in Software Product Lines. There are alternative notations reported in the literature to represent feature models. Compared to the graphical notations, the text-based notations are more amenable to automated processing and tool interoperability. This study presents an XML-based feature modeling language to represent extended feature models that can include complex relationships involving attributes. We first provide a Context Free ...
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...
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...
Regression analysis with a dtochastic design variable Sazak, HS; Tiku, ML; İslam, Muhammed Qamarul (Wiley, 2006-04-01) In regression models, the design variable has primarily been treated as a nonstochastic variable. In numerous situations, however, the design variable is stochastic. The estimation and hypothesis testing problems in such situations are considered. Real life examples are given.

Citation Formats

L. NABDEL, A. S. Karatas, M. H. S. Oğuztüzün, and A. Dogru, “FMML: A Feature Model Markup Language,” 2011, vol. 1389, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47501.