A text-based approach to feature modelling: Syntax and semantics of TVL

Classen, Andreas; Boucher, Quentin; Heymans, Patrick

doi:10.1016/j.scico.2010.10.005

Cited by 129 publications

(108 citation statements)

References 19 publications

Supporting

Mentioning

106

Contrasting

Unclassified

Order By: Relevance

“…Our toolkit also includes a converter that provides bidirectional translation between FAMILIAR and different formats (SPLOT [45], FeatureIDE [36], S2T2 [60,57], TVL [16], etc.). This allows the architectural FMs derived by our approach to be immediately visualized and used as input of subsequent software configuration or generation tasks.…”

Section: Tool Supportmentioning

confidence: 99%

Extraction and evolution of architectural variability models in plugin-based systems

et al. 2013

View full text Add to dashboard Cite

Variability management is a key issue when building and evolving software-intensive systems, making it possible to extend, configure, customize and adapt such systems to customers' needs and specific deployment contexts. A wide form of variability can be found in extensible software systems, typically built on top of plugin-based architectures that offer a (large) number of configuration options through plugins. In an ideal world, a software architect should be able to generate a system variant on-demand, corresponding to a particular assembly of plugins. To this end, the variation points and constraints between architectural elements should be properly modeled and maintained over time (i.e., for each version of an architecture). A crucial, yet errorprone and time-consuming, task for a software architect is to build an accurate representation of the variability of an architecture, in order to prevent unsafe architectural variants and reach the highest possible level of flexibility. In this article, we propose a reverse engineering process for producing a variability model (i.e., a feature model) of a plugin-based architecture. We develop automated techniques to extract and combine different variability descriptions, including a hierarchical software architecture model, a plugin dependency model and the software architect knowledge. By computing and reasoning about differences between versions of architectural feature models, software architect can control both the variability extraction and evolution processes. The proSend offprint requests to: posed approach has been applied to a representative, large-scale plugin-based system (FraSCAti), considering different versions of its architecture. We report on our experience in this context.

show abstract

Section: Tool Supportmentioning

confidence: 99%

Extraction and evolution of architectural variability models in plugin-based systems

et al. 2013

View full text Add to dashboard Cite

show abstract

“…For instance, TVL (Text-based Variability Language) is a textual VML inspired in FMs whose syntax and semantics are formally presented in [18]. The semantics of TVL are represented as the set of products described by an instance of the language.…”

Section: Related Workmentioning

confidence: 99%

FLAME: a formal framework for the automated analysis of software product lines validated by automated specification testing

et al. 2015

View full text Add to dashboard Cite

In a literature review on the last 20 years of automated analysis of feature models, the formalization of analysis operations was identified as the most relevant challenge in the field. This formalization could provide very valuable assets for tool developers such as a precise definition of the analysis operations and, what is more, a reference implementation, i.e. a trustworthy, not necessarily efficient implementation to compare different tools outputs. In this article, we present the FLAME framework as the result of facing this challenge. FLAME is a formal framework that can be used to formally specify not only feature models, but other variability modeling languages (VMLs) as well. This reusability is achieved by its two-layered architecture. The abstract foundation layer is the bottom layer in which all VMLindependent analysis operations and concepts are specified. On top of the foundation layer, a family of characteristic model layers-one for each VML to be formally specifiedcan be developed by redefining some abstract types and relations. The verification and validation of FLAME has fol- lowed a process in which formal verification has been performed traditionally by manual theorem proving, but validation has been performed by integrating our experience on metamorphic testing of variability analysis tools, something that has shown to be much more effective than manuallydesigned test cases. To follow this automated, test-based validation approach, the specification of FLAME, written in Z, was translated into Prolog and 20,000 random tests were automatically generated and executed. Tests results helped to discover some inconsistencies not only in the formal specification, but also in the previous informal definitions of the analysis operations and in current analysis tools. After this process, the Prolog implementation of FLAME is being used as a reference implementation for some tool developers, some analysis operations have been formally specified for the first time with more generic semantics, and more VMLs are being formally specified using FLAME.

show abstract

“…This section introduces the µTVL text-based feature modelling language, pronounced either micro textual variability language or simply mu tee vee ell, an extended subset of TVL [7,11]. TVL was developed at the University of Namur, Belgium, to serve as a reference language for specifying feature models.…”

Section: Feature Modellingmentioning

confidence: 99%

“…Expressions e are encoded into constraints, denoted φ e . Their encoding is straightforward and therefore omitted (see [11]). Boolean operations are mapped to a conjunctive set of integer operations over the values 0 and 1 where, for example, a → b is a shorthand for a ≤ b.…”

Section: Semanticsmentioning

confidence: 99%

See 1 more Smart Citation

Variability Modelling in the ABS Language

Clarke

Muschevici

Proença

et al. 2011

Formal Methods for Components and Objects

View full text Add to dashboard Cite

Abstract. The HATS project aims at developing a model-centric methodology for the design, implementation and verification of highly configurable systems, such as software product lines, centred around the Abstract Behavioural Specification (ABS) modelling Language. This article describes the variability modelling features of the ABS Modelling framework. It consists of four languages, namely, µTVL for describing feature models at a high level of abstraction, the Delta Modelling Language DML for describing variability of the 'code' base in terms of delta modules, the Product Line Configuration Language CL for linking feature models and delta modules together and the Product Selection Language PSL for describing a specific product to extract from a product line. Both formal semantics and examples of each language are presented.

show abstract

A text-based approach to feature modelling: Syntax and semantics of TVL

Cited by 129 publications

References 19 publications

Extraction and evolution of architectural variability models in plugin-based systems

Extraction and evolution of architectural variability models in plugin-based systems

FLAME: a formal framework for the automated analysis of software product lines validated by automated specification testing

Variability Modelling in the ABS Language

Contact Info

Product

Resources

About