Feature Model Differences

International audienceFeature models are a widespread means to represent commonality and variability in software product lines. As is the case for other kinds of models, computing and managing feature model differences is useful in various real-world situations. In this paper, we propose a set of novel differencing techniques that combine syntactic and semantic mechanisms, and automatically produce meaningful differences. Practitioners can exploit our results in various ways: to understand, manipulate, visualize and reason about differences. They can also combine them with existing feature model composition and decomposition operators. The proposed automations rely on satisfiability algorithms. They come with a dedicated language and a comprehensive environment. We illustrate and evaluate the practical usage of our techniques through a case study dealing with a configurable component framework

Modèles de caractéristiques augmentés de cardinalités relatives

Feature modeling is widely used to capture and manage commonalities and variabilities in software product lines.Cardinality-based feature models are used when variability applies not only to the selection or exclusion of features but also to the number of times a feature can be included in a product.Feature cardinalities are usually considered to apply in local or global scope. However, through our work in managing variability in cloud computing providers, we have identified cases where these interpretations are insufficient to capture the variability of the cloud environment.In this paper, we redefine cardinality-based feature models to allow multiple relative cardinalities between features and discuss the effects of relative cardinalities on cross-tree constraints.To evaluate our approach we conducted an analysis of relative cardinalities in four cloud computing providers.In addition, we developed tools for reasoning on feature models with relative cardinalities and performed experiments to verify the performance and scalability of the approach.The results from our study indicate that extending feature models with relative cardinalities is feasible and improves variability modeling, especially in the case of cloud environments

Implementing Feature Variability for Models and Code with Projectional Language Workbenches

Abstract Product line engineering deals with managing and implementing the variability among a set of related products. We distinguish between two kinds of variability: configuration and customization. Customization variability can be described using programming language code or creative construction DSLs, whereas configuration variability is described using configuration based approaches, such as feature models. Many product lines have both kinds of variability, and they need to be integrated efficiently. This paper describes an approach for product line engineering using projectional language workbenches. These represent code and models with the same fundamental technology, enabling the mixing of models and code. They make the tight integration between several domain-specific languages possible and simple. Since they can store arbitrary information in models, it is possible to overlay configuration variability over customization variability (i.e. apply feature model-based configuration to code and models). Because of the projectional approach to editing, programs can be shown with or without the dependencies on feature models, they can even be rendered (and edited) for a specific variant. This approach leads to highly integrated and productive tools for product line development. The paper explains the approach, outlines the implementation of a prototype tool based on Jetbrains MPS and illustrates the benefits using a small product line for embedded systems

Integrating the common variability language with multilanguage annotations for web engineering

Web applications development involves managing a high diversity of files and resources like code, pages or style sheets, implemented in different languages. To deal with the automatic generation of custom-made configurations of web applications, industry usually adopts annotation-based approaches even though the majority of studies encourage the use of composition-based approaches to implement Software Product Lines. Recent work tries to combine both approaches to get the complementary benefits. However, technological companies are reticent to adopt new development paradigms such as feature-oriented programming or aspect-oriented programming. Moreover, it is extremely difficult, or even impossible, to apply these programming models to web applications, mainly because of their multilingual nature, since their development involves multiple types of source code (Java, Groovy, JavaScript), templates (HTML, Markdown, XML), style sheet files (CSS and its variants, such as SCSS), and other files (JSON, YML, shell scripts). We propose to use the Common Variability Language as a composition-based approach and integrate annotations to manage fine grained variability of a Software Product Line for web applications. In this paper, we (i) show that existing composition and annotation-based approaches, including some well-known combinations, are not appropriate to model and implement the variability of web applications; and (ii) present a combined approach that effectively integrates annotations into a composition-based approach for web applications. We implement our approach and show its applicability with an industrial real-world system.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Feature-Oriented Modelling Using Event-B

Event-B is a formal method for specification and verification of reactive systems. Its Rodin toolkit provides comprehensive support for modelling, refinement and analysis using theorem proving, animation and model checking. There has always been a need to reuse existing models and their associated proofs when modelling related systems to save time and effort. Software product lines (SPLs) focus on the problem of reuse by providing ways to build software products having commonalities and managing variations within products of the same family. Feature modelling is a well know technique to manage variability and configure products within the SPLs. We have combined the two approaches to formally specify SPLs using Event-B. This will contribute the concept of formalism to SPLs and re-usability to Event-B. Existing feature modelling notations were adapted and extended to include refinement mechanism of Event-B. An Eclipse-based graphical feature modelling tool has been developed as a plug-in to the Rodin platform. We have modelled the "production cell" case-study in Event-B, an industrial metal processing plant, which has previously been specified in a number of formalisms. We have also highlighted future directions based on our experience with this framework so far

Product Line Architecture for Automatic Evolution of Multi-Tenant Applications

Cloud computing is becoming the predominant mechanism to seamlessly deploy applications with special requirements such as massive storage sharing or load balancing, usually provided as services by cloud platforms. A developer can improve the application’s delivery and productivity by following a multi tenancy approach, where variants of the same application can be quickly customized to the necessities of each tenant. However, managing the inherent variability existing in multitenant applications and, even more importantly, managing the evolution of a multi-tenant application with hundreds of tenants and thousands of different valid architectural configurations can become intractable if performed manually. In this paper we propose a product line architecture approach in which: (1) we use cardinality-based variability models to model each tenant as a clonable feature, (2) we automate the process of evolving the multi-tenant application architecture, and (3) we demonstrate that the implemented process is correct and efficient for a high number of tenants in a reasonable time. We use a running case study in the domain of medical software.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Composition and Self-Adaptation of Service-Based Systems with Feature Models

The adoption of mechanisms for reusing software in pervasive systems has not yet become standard practice. This is because the use of pre-existing software requires the selection, composition and adaptation of prefabricated software parts, as well as the management of some complex problems such as guaranteeing high levels of efficiency and safety in critical domains. In addition to the wide variety of services, pervasive systems are composed of many networked heterogeneous devices with embedded software. In this work, we promote the safe reuse of services in service-based systems using two complementary technologies, Service-Oriented Architecture and Software Product Lines. In order to do this, we extend both the service discovery and composition processes defined in the DAMASCo framework, which currently does not deal with the service variability that constitutes pervasive systems. We use feature models to represent the variability and to self-adapt the services during the composition in a safe way taking context changes into consideration. We illustrate our proposal with a case study related to the driving domain of an Intelligent Transportation System, handling the context information of the environment.Work partially supported by the projects TIN2008-05932, TIN2008-01942, TIN2012-35669, TIN2012-34840 and CSD2007-0004 funded by Spanish Ministry of Economy and Competitiveness and FEDER; P09-TIC-05231 and P11-TIC-7659 funded by Andalusian Government; and FP7-317731 funded by EU. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Composing your Compositions of Variability Models

International audienceModeling and managing variability is a key activity in a growing number of software engineering contexts. Support for composing variability models is arising in many engineering scenarios, for instance, when several subsystems or modeling artifacts, each coming with their own variability and possibly developed by different stakeholders, should be combined together. In this paper, we consider the problem of composing feature models (FMs), a widely used formalism for representing and reasoning about a set of variability choices. We show that several composition operators can actually be defined, depending on both matching/merging strategies and semantic properties expected in the composed FM. We present four alternative forms and their implementations. We discuss their relative trade-offs w.r.t. reasoning, customizability, traceability, composability and quality of the resulting feature diagram. We summarize these findings in a reading grid which is validated by revisiting some relevant existing works. Our contribution should assist developers in choosing and implementing the right composition operators

A Model-Based Approach to Managing Feature Binding Time in Software Product Line Engineering

Software Product Line Engineering (SPLE) is a software reuse paradigm for developing software products, from managed reusable assets, based on analysis of commonality and variability (C & V) of a product line. Many approaches of SPLE use a feature as a key abstraction to capture the C&V. Recently, there have been increasing demands for the provision of flexibility about not only the variability of features but also the variability of when features should be selected (i.e., variability on feature binding times). Current approaches to support variations of feature binding time mostly focused on ad hoc implementation mechanisms. In this paper, we first identify the challenges of feature binding time management and then propose an approach to analyze the variation of feature binding times and use the results to specify model-based architectural components for the product line. Based on the specification, components implementing variable features are parameterized with the binding times and the source codes for the components and the connection between them are generated