The Model-Driven Architecture (MDA) [Fra03] is an initiative by the Object Management Group (OMG) to define an approach to software development based on modeling and automated mapping of models to implementations. The basic MDA pattern involves defining a platformindependent model (PIM) and its automated mapping to one or more platform-specific models

Abstract. Feature models are used to specify members of a product-line. Despite years of progress, contemporary tools provide limited support for feature constraints and offer little or no support for debugging feature models. We integrate prior results to connect feature models, grammars, and propositional formulas. This connection allows arbitrary propositional constraints to be defined among features and enables off-the-shelf satisfiability solvers to debug feature models. We also show how our ideas can generalize recent results on the staged configuration of feature models.

Abstract. This paper is about a paradigm shift from the current practice of manually searching for and adapting components and their manual assembly to Generative Programming, which is the automatic selection and assembly of components on demand. First, we argue that the current OO technology does not support reuse and configurability in an effective way. Then we show how a system family approach can aid in defining reusable components. Finally, we describe how to automate the assembly of components based on configuration knowledge. We compare this paradigm shift to the introduction of interchangeable parts and automated assembly lines in the automobile industry. We also illustrate the steps necessary to develop a product line using a simple example of a car product line. We present the feature model of the product line, develop a layered architecture for it, and automate the assembly of the components using a generator. We also discuss some design issues, applicability of the approach, and future development. 1 From Handcrafting to an Automated Assembly Line This paper is about a paradigm shift from the current practice of manually searching for and adapting components and their manual assembly to Generative Programming,

Abstract. Although a feature model can represent commonalities and variabilities in a very concise taxonomic form, features in a feature model are merely symbols. Mapping features to other models, such as behavioral or data specifications, gives them semantics. In this paper, we propose a general template-based approach for mapping feature models to concise representations of variability in different kinds of other models. We show how the approach can be applied to UML 2.0 activity and class models and describe a prototype implementation. 1

"In order to reuse software, there needs to be software to reuse." -- Tracz [9] One of the dilemmas that has prevented software developers from reusing software is the lack of software artifacts to use or the existence of artifacts that are difficult to integrate. Domain-Specific Software Architectures (DSSAs) have been proposed[4] in order to address these issues. A DSSA not only provides a framework for reusable software components to fit into, but captures the design rationale and provides for a degree of adaptability. This paper 1 presents an outline for a DomainSpecific Software Architecture engineering process. Keywords: Domain Analysis, Domain Specific Software Architecture, Domain Engineering Introduction The purpose of the paper is to outline the domainengineering process 2 being used to generate a Domain-Specific Software Architecture (DSSA) as part the DARPA DSSA-ADAGE (Avionics Domain Application Generation Environment) Project 3 . It is based 1 A previous version...

Abstract Feature modeling is an important approach to capture the commonalities and variabilities in system families and product lines. Cardinality-based feature modeling integrates a number of existing extensions of the original feature-modeling notation from Feature-Oriented Domain Analysis. Staged configuration is a process that allows the incremental configuration of cardinality-based feature models. It can be achieved by performing a step-wise specialization of the feature model. In this paper, we argue that cardinality-based feature models can be interpreted as a special class of context-free grammars. We make this precise by specifying a translation from a feature model into a context-free grammar. Consequently, we provide a semantic interpretation for cardinalitybased feature models by assigning an appropriate semantics to the language recognized by the corresponding grammar. Finally, we give an account on how feature model specialization can be formalized as transformations on the grammar equivalent of feature models.

Software Product Line (SPL) Engineering has proved to be an effective method for software production. However, in the SPL community it is well recognized that variability in SPLs is increasing by the thousands. Hence, an automatic support is needed to deal with variability in SPL. Most of the current proposals for automatic reasoning on SPL are not devised to cope with extra-functional features. In this paper we introduce a proposal to model and reason on an SPL using constraint programming. We take into account functional and extra-functional features, improve current proposals and present a running, yet feasible implementation.

Model transformations are touted to play a key role in Model Driven Developmente. Although well-established standards for creating metamodels such as the Meta-Object Facility exist, there is currently no mature foundation for specifying transformations among models. We propose a framework for the classification of several existing and proposed model transformation approaches. The classification framework is given as a feature model that makes explicit the different design choices for model transformations. Based on our analysis of model transformation approaches, we propose a few major categories in which most approaches fit.

Abstract Feature modeling is a key technique for capturing commonalities and variabilities in system families and product lines. In this paper, we propose a cardinality-based notation for feature modeling, which integrates a number of existing extensions of previous approaches. We then introduce and motivate the novel concept of staged configuration. Staged configuration can be achieved by the stepwise specialization of feature models or by multi-level configuration, where the configuration choices available in each stage are defined by separate feature models. Staged configuration is important because in a realistic development process, different groups and different people make product configuration choices in different stages. Finally, we also discuss how multi-level configuration avoids a breakdown between the different abstraction levels of individual features. This problem, sometimes referred to as “analysis paralysis”, easily occurs in feature modeling because features can denote entities at arbitrary levels of abstractions within a system family. Key words: Software product lines, system families, domain analysis, software configuration

Abstract. Feature modeling is an important approach to capturing commonalities and variabilities in system families and product lines. In this paper, we propose a cardinality-based notation for feature modeling, which integrates a number of existing extensions of previous approaches. We then introduce and motivate the novel concept of staged configuration. Staged configuration can be achieved by the stepwise specialization of feature models. This is important because in a realistic development process, different groups and different people eliminate product variability in different stages. We also indicate how cardinality-based feature models and their specialization can be given a precise formal semantics. 1