Automated analysis of feature models: Quo vadis?

Feature models have been used since the 90's to describe software product lines as a way of reusing common parts in a family of software systems. In 2010, a systematic literature review was published summarizing the advances and settling the basis of the area of Automated Analysis of Feature Models (AAFM). From then on, different studies have applied the AAFM in different domains. In this paper, we provide an overview of the evolution of this field since 2010 by performing a systematic mapping study considering 423 primary sources. We found six different variability facets where the AAFM is being applied that define the tendencies: product configuration and derivation; testing and evolution; reverse engineering; multi-model variability-analysis; variability modelling and variability-intensive systems. We also confirmed that there is a lack of industrial evidence in most of the cases. Finally, we present where and when the papers have been published and who are the authors and institutions that are contributing to the field. We observed that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are published. We also suggest some synergies with other areas such as cloud or mobile computing among others that can motivate further research in the future.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía TIC-186

Using problem descriptions to represent variabilities for context-aware applications

This paper investigates the potential use of problem descriptions to represent and analyse variability in context-aware software products. By context-aware, we refer to recognition of changes in properties of external domains, which are recognised as affecting the behaviour of products. There are many reasons for changes in the operating environment, from fluctuating resources upon which the product relies, to different operating locations or the presence of objects. There is an increasing expectation for software intensivedevices to be context-aware which, in turn, adds further variability to problem description and analysis. However, we argue in this paper that the capture of contextual variability on current variability representations and analyses has yet to be explored. We illustrate the representation of this type of variability in a pilot study, and conclude with lessons learnt and an agenda for further work

A Systematic Review of Tracing Solutions in Software Product Lines

Software Product Lines are large-scale, multi-unit systems that enable massive, customized production. They consist of a base of reusable artifacts and points of variation that provide the system with flexibility, allowing generating customized products. However, maintaining a system with such complexity and flexibility could be error prone and time consuming. Indeed, any modification (addition, deletion or update) at the level of a product or an artifact would impact other elements. It would therefore be interesting to adopt an efficient and organized traceability solution to maintain the Software Product Line. Still, traceability is not systematically implemented. It is usually set up for specific constraints (e.g. certification requirements), but abandoned in other situations. In order to draw a picture of the actual conditions of traceability solutions in Software Product Lines context, we decided to address a literature review. This review as well as its findings is detailed in the present article.Comment: 22 pages, 9 figures, 7 table

Clafer: Lightweight Modeling of Structure, Behaviour, and Variability

Embedded software is growing fast in size and complexity, leading to intimate mixture of complex architectures and complex control. Consequently, software specification requires modeling both structures and behaviour of systems. Unfortunately, existing languages do not integrate these aspects well, usually prioritizing one of them. It is common to develop a separate language for each of these facets. In this paper, we contribute Clafer: a small language that attempts to tackle this challenge. It combines rich structural modeling with state of the art behavioural formalisms. We are not aware of any other modeling language that seamlessly combines these facets common to system and software modeling. We show how Clafer, in a single unified syntax and semantics, allows capturing feature models (variability), component models, discrete control models (automata) and variability encompassing all these aspects. The language is built on top of first order logic with quantifiers over basic entities (for modeling structures) combined with linear temporal logic (for modeling behaviour). On top of this semantic foundation we build a simple but expressive syntax, enriched with carefully selected syntactic expansions that cover hierarchical modeling, associations, automata, scenarios, and Dwyer's property patterns. We evaluate Clafer using a power window case study, and comparing it against other notations that substantially overlap with its scope (SysML, AADL, Temporal OCL and Live Sequence Charts), discussing benefits and perils of using a single notation for the purpose

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

Detecting and Explaining Conflicts in Attributed Feature Models

Product configuration systems are often based on a variability model. The development of a variability model is a time consuming and error-prone process. Considering the ongoing development of products, the variability model has to be adapted frequently. These changes often lead to mistakes, such that some products cannot be derived from the model anymore, that undesired products are derivable or that there are contradictions in the variability model. In this paper, we propose an approach to discover and to explain contradictions in attributed feature models efficiently in order to assist the developer with the correction of mistakes. We use extended feature models with attributes and arithmetic constraints, translate them into a constraint satisfaction problem and explore those for contradictions. When a contradiction is found, the constraints are searched for a set of contradicting relations by the QuickXplain algorithm.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301

Synthesis of Attributed Feature Models From Product Descriptions: Foundations

Feature modeling is a widely used formalism to characterize a set of products (also called configurations). As a manual elaboration is a long and arduous task, numerous techniques have been proposed to reverse engineer feature models from various kinds of artefacts. But none of them synthesize feature attributes (or constraints over attributes) despite the practical relevance of attributes for documenting the different values across a range of products. In this report, we develop an algorithm for synthesizing attributed feature models given a set of product descriptions. We present sound, complete, and parametrizable techniques for computing all possible hierarchies, feature groups, placements of feature attributes, domain values, and constraints. We perform a complexity analysis w.r.t. number of features, attributes, configurations, and domain size. We also evaluate the scalability of our synthesis procedure using randomized configuration matrices. This report is a first step that aims to describe the foundations for synthesizing attributed feature models