Supporting multiple perspectives in feature-based configuration

Hubaux, Arnaud; Heymans, Patrick; Schobbens, Pierre‐Yves; Deridder, Dirk; Abbasi, Ebrahim

doi:10.1007/s10270-011-0220-1

Cited by 41 publications

(34 citation statements)

References 30 publications

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“…In the context of feature-based configuration, techniques have been proposed to separate the configuration process in different steps or stages [19]. Hubaux et al provide view mechanisms to decompose a large FM [32]. However they do not propose a comprehensive solution when dealing with cross-tree constraints.…”

Section: Related Workmentioning

confidence: 99%

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

et al. 2013

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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.

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Section: Related Workmentioning

confidence: 99%

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

et al. 2013

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“…The sought benefits are indeed similar to the ones of software engineering disciplines, i.e., reduced complexity, improved reusability and simpler evolution [61]. A possible way to achieve SoC is then to rely on views, i.e., simplified representations of an FM tailored for a specific stakeholder, role, or task [36]. Views facilitate the decision-making process in that they only focus on those parts of the FM that are relevant for a given concern.…”

Section: Introductionmentioning

confidence: 98%

Separating Concerns in Feature Models: Retrospective and Support for Multi-Views

et al. 2013

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Feature models (FMs) are a popular formalism to describe the commonality and variability of a set of assets in a software product line (SPL). SPLs usually involve large and complex FMs that describe thousands of features whose legal combinations are governed by many and often complex rules. The size and complexity of these models is partly explained by the large number of concerns considered by SPL practitioners when managing and configuring FMs. In this chapter, we first survey concerns and their separation in FMs, highlighting the need for more modular and scalable techniques. We then revisit the concept of view as a simplified representation of an FM. We finally describe a set of techniques to specify, visualize and verify the coverage of a set of views. These techniques are implemented in complementary tools providing practical support for feature-based configuration and large scale management of FMs.

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“…The core idea of proposed algorithm is to compute proposition formula representing the set of configuration and rules and to apply propositional logic reasoning techniques to construct an FM (representing its hierarchy, variability information, feature groups and cross-tree constraints).By extended the previous author [31] also proposed the concept that how set of complementary set of operators like aggregate, merge and slice can provide practically and efficient support for separation of concerns from feature modeling. They defined that slicing process is both semantic and syntactic so they analyze the cross-cutting constraints to define the features that must be or cannot be sliced.…”

Section: Using Feature Based Criteriamentioning

confidence: 99%

Literature Analysis on Model based Slicing

Singh¹,

Arora²

2013

IJCA

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To understand and test a large software product is very challenging task. One way to ease this is program slicing technique that decomposes the large programs into smaller ones and another is model based slicing that decomposes the large software architecture model into smaller models at the early stage of SDLC (Software Development Life Cycle). This literature analysis presents an overview of Model based slicing, including the various general approaches and techniques used to compute slices.

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Supporting multiple perspectives in feature-based configuration

Cited by 41 publications

References 30 publications

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

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

Separating Concerns in Feature Models: Retrospective and Support for Multi-Views

Literature Analysis on Model based Slicing

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