Automated Analysis in Feature Modelling and Product Configuration

The automated analysis of feature models is one of the thriving topics of research in the software product line and variability management communities that has attracted more attention in the last years. A recent literature review reported that more than 30 analysis operations have been identi ed and di erent analysis mechanisms have been proposed. Product con guration is a well established research eld with more than 30 years of successful applications in di erent industrial domains. Our hypothesis, that is not really new, is that these two independent areas of research have interesting synergies that have not been fully explored. To try to explore the potential synergies systematically, in this paper we provide a rapid review to bring together these previously disparate streams of work. We de ne a set of research questions and give a preliminary answer to some of them. We conclude that there are many research opportunities in the synergy of these independent areas.Ministerio de Ciencia e Innovación TIN2009- 07366Junta de Andalucía TIC-590

Towards an ontology-based approach for deriving product architectures

Software product line (SPL) engineering has proven to improve software quality and shorten costs and development time. An important aspect in the product line development process involves variability, which is the ability of a system for being customised, changed, or extended. Approaches are required for modelling and resolving variability as well as for verifying the selections. In this paper, we outline our ongoing research towards an approach that automates the derivation of product architectures from an SPL architecture. The proposed approach relies on ontology-based reasoning and model-driven techniques, the former supports the validation of the generated architectures and the generation of the transformation rules while the latter realises the actual target product architectures. We sketch our approach with a voice over IP case example. Copyright � 2011 ACM

Reverse Engineering Architectural Feature Models

International audienceReverse engineering the variability of an existing system is a challenging activity. The architect knowledge is essential to identify variation points and explicit constraints between features, for instance in feature models (FMs), but the manual creation of FMs is both timeconsuming and error-prone. On a large scale, it is very difficult for an architect to guarantee that the resulting FM ensures a safe composition of the architectural elements when some features are selected. In this paper, we present a comprehensive, tool supported process for reverse engineering architectural FMs. We develop automated techniques to extract and combine different variability descriptions of an architecture. Then, alignment and reasoning techniques are applied to integrate the architect knowledge and reinforce the extracted FM. We illustrate the reverse engineering process when applied to a representative software system, FraSCAti, and we report on our experience in this context

Improving the Testing and Testability of Software Product Lines

Abstract. Software Product Line (SPL) engineering offers several advantages in the development of families of software products. There is still a need, however, for better understanding of testability issues and for testing techniques that can operate cost-effectively on SPLs. In this paper we consider these testability issues and highlight some differences between optional versus alternative features. We then provide a graph based testing approach called the FIG Basis Path method that selects products and features for testing based on a feature dependency graph. We conduct a case study on several non-trivial SPLs and show that for these subjects, the FIG Basis Path method is as effective as testing all products, but tests no more than 24 % of the products in the SPL.

Feature models, grammars, and propositional formulas

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

Reducing Configurations to Monitor in a Software Product Line

Abstract. A software product line is a family of programs where each program is defined by a unique combination of features. Product lines, like conventional programs, can be checked for safety properties through execution monitoring. However, because a product line induces a number of programs that is potentially exponential in the number of features, it would be very expensive to use existing monitoring techniques: one would have to apply those techniques to every single program. Doing so would also be wasteful because many programs can provably never violate the stated property. We introduce a monitoring technique dedicated to product lines that, given a safety property, statically determines the feature combinations that cannot possibly violate the property, thus reducing the number of programs to monitor. Experiments show that our technique is effective, particularly for safety properties that crosscut many optional features.

Foundations of Coloring Algebra with Consequences for Feature-Oriented Programming

Abstract. In 2011, simple and concise axioms for feature compositions, interactions and products have been proposed by Batory et al. They were mainly inspired by Kästner’s Colored IDE (CIDE) as well as by experience in feature oriented programming over the last decades. However, so far only axioms were proposed; consequences of these axioms such as variability in models have not been studied. In this paper we discuss the proposed axioms from a theoretical point of view, which yields a much better understanding of the proposed algebra and therefore of feature oriented programming. For example, we show that the axioms characterising feature composition are isomorphic to set-theoretic models.

Detecting inconsistencies in multi-view models with variability

Abstract. Multi-View Modeling (MVM) is a common modeling practice that advocates the use of multiple, different and yet related models to represent the needs of diverse stakeholders. Of crucial importance in MVM is consistency checking — the description and verification of semantic relationships amongst the views. Variability is the capacity of software artifacts to vary, and its effective management is a core tenet of the research in Software Product Lines (SPL). MVM has proven useful for developing one-of-a-kind systems; however, to reap the potential benefits of MVM in SPL it is vital to provide consistency checking mechanisms that cope with variability. In this paper we describe how to address this need by applying Safe Composition — the guarantee that all programs of a product line are type safe. We evaluate our approach with a case study.