Model Construction with External Constraints: An Interactive Journey from Semantics to Syntax

Janota, Mikoláš; Kuzina, V.V; Wąsowski, Andrzej

doi:10.1007/978-3-540-87875-9_31

Cited by 25 publications

(22 citation statements)

References 16 publications

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“…The kernel configurator renders the model as a tree of options, which users select to specify the configuration to be built. Figure 1 shows a fragment of the Linux variability model, containing a menu (line 1) with two Boolean configs as children: PM (lines [3][4][5] and PM_SLEEP (lines 9-13). Configs are named parameters with a specified type.…”

Section: The Linux Kernel and Its Variability Modelmentioning

confidence: 99%

“…Nevertheless, evolution of real variability models has not been studied. Multiple authors have been interested in reasoning about feature model editing [2,3], in semantics of feature model refactorings [4], or in synchronizing artifacts in product lines [5,6], which indeed, as we shall see, is a major challenge in maintaining a variability model. However, none of these works was driven by documented challenges faced by practitioners.…”

Section: Introductionmentioning

confidence: 99%

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Evolution of the Linux Kernel Variability Model

Lotufo

She

Berger

et al. 2010

Lecture Notes in Computer Science

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104

111

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Abstract. Understanding the challenges faced by real projects in evolving variability models, is a prerequisite for providing adequate support for such undertakings. We study the evolution of a model describing features and configurations in a large product line-the Linux kernel variability model. We analyze this evolution quantitatively and qualitatively. Our primary finding is that the Linux kernel model appears to evolve surprisingly smoothly. In the analyzed period, the number of features had doubled, and still the structural complexity of the model remained roughly the same. Furthermore, we provide an in-depth look at the effect of the kernel's development methodologies on the evolution of its model. We also include evidence about edit operations applied in practice, evidence of challenges in maintaining large models, and a range of recommendations (and open problems) for builders of modeling tools.

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Section: The Linux Kernel and Its Variability Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evolution of the Linux Kernel Variability Model

Lotufo

She

Berger

et al. 2010

Lecture Notes in Computer Science

Self Cite

104

111

View full text Add to dashboard Cite

show abstract

“…In [3], poor design patterns are detected by using off-the-shelf CSP techniques and tools. [37] defines an interactive guided derivation algorithm to assist model designers by providing hints about valid editing operations that maintain global correctness of models.…”

Section: Related Workmentioning

confidence: 99%

Dynamic constraint satisfaction problems over models

Horváth

Varró

2011

Softw Syst Model

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In early phases of designing complex systems, models are not sufficiently detailed to serve as an input for automated synthesis tools. Instead, a design space is constituted by multiple models representing different valid design candidates. Design space exploration aims at searching through these candidates defined in the design space to find solutions that satisfy the structural and numeric design constraints and provide a balanced choice with respect to various quality metrics. Design space exploration in an modeldriven engineering (MDE) context is frequently tackled as specific sort of constraint satisfaction problem (CSP). In CSP, declarative constraints capture restrictions over variables with finite domains where both the number of variables and their domains are required to be a priori finite. However, the existing formulation of constraint satisfaction problems can be too restrictive to capture design space exploration in many MDE applications with complex structural constraints expressed over the underlying models. In this paper, we interpret flexible and dynamic constraint satisfaction problems directly in the context of models. These extensions allow the relaxation of constraints during a solving process and address problems that are subject to change and require Communicated by Andy Schuerr and Bran Selic.incremental re-evaluation. Furthermore, we present our prototype constraint solver for the domain of graph models built upon the Viatra2 model transformation framework and provide an evaluation of its performance with comparison to related tools.

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“…The two synthesis steps are executed consecutively in this scenario yielding a feature graph. The final FM is built using an interactive FM building tool that uses the FG as a guide [26]. This scenario is an example of FM synthesis where the FM hierarchy is decided at a later time, after the FG is constructed.…”

Section: Overview and Motivationmentioning

confidence: 99%

“…His framework would experience a significant performance boost if employing our new algorithms. Janota et al [26] propose an interactive tool for building feature models from propositional formulas. The tool uses a feature graph synthesized using [16] to determine the editing operations that create valid feature diagrams.…”

Section: Related Workmentioning

confidence: 99%

Efficient synthesis of feature models

Andersen

Czarnecki

She

et al. 2012

Proceedings of the 16th International Software Product Line Conference - Volume 1

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Variability modeling, and in particular feature modeling, is a central element of model-driven software product line architectures. Such architectures often emerge from legacy code, but, unfortunately creating feature models from large, legacy systems is a long and arduous task.We address the problem of automatic synthesis of feature models from propositional constraints. We show that this problem is NP-hard. We design efficient techniques for synthesis of models from respectively CNF and DNF formulas, showing a 10-to 1000-fold performance improvement over known techniques for realistic benchmarks.Our algorithms are the first known techniques that are efficient enough to be applied to dependencies extracted from real systems, opening new possibilities of creating reverse engineering and model management tools for variability models. We discuss several such scenarios in the paper.

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Model Construction with External Constraints: An Interactive Journey from Semantics to Syntax

Cited by 25 publications

References 16 publications

Evolution of the Linux Kernel Variability Model

Evolution of the Linux Kernel Variability Model

Dynamic constraint satisfaction problems over models

Efficient synthesis of feature models

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