Family-Based Model Checking with mCRL2

Beek, Maurice H. ter; Vink, Erik P. de; Willemse, Tim A. C.

doi:10.1007/978-3-662-54494-5_23

Cited by 34 publications

(37 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Examples of such SPL model checkers are SNIP and ProVeLines by the team of [12] that are derived from SPIN. However, the mCRL2 toolset as-is, without specific modifications, has also been used to compare product-based vs. family-based model checking [3,5,7]. For this, the extension of the modal μ-calculus for the analysis of FTSes proposed in [4], that combines actions and feature expressions for its modalities, was translated into the first-order μ-calculus [25], the property language of the mCRL2 toolset.…”

Section: Software Product Linesmentioning

confidence: 99%

The mCRL2 Toolset for Analysing Concurrent Systems

Bunte

Groote

Keiren

et al. 2019

Tools and Algorithms for the Construction and Analysis of Systems

Self Cite

100

View full text Add to dashboard Cite

Reasoning about the correctness of parallel and distributed systems requires automated tools. By now, the mCRL2 toolset and language have been developed over a course of more than fifteen years. In this paper, we report on the progress and advancements over the past six years. Firstly, the mCRL2 language has been extended to support the modelling of probabilistic behaviour. Furthermore, the usability has been improved with the addition of refinement checking, counterexample generation and a user-friendly GUI. Finally, several performance improvements have been made in the treatment of behavioural equivalences. Besides the changes to the toolset itself, we cover recent applications of mCRL2 in software product line engineering and the use of domain specific languages (DSLs).1 The source code is also archived on https://doi.org/10.5281/zenodo.2555054.

show abstract

Section: Software Product Linesmentioning

confidence: 99%

The mCRL2 Toolset for Analysing Concurrent Systems

Bunte

Groote

Keiren

et al. 2019

Tools and Algorithms for the Construction and Analysis of Systems

Self Cite

100

View full text Add to dashboard Cite

show abstract

“…This approach is extended [9,6] to enable verification of CTL properties using an family-based version of NuSMV. The work [4] shows how modal µ-calculus properties of variational systems can be verified using a general-purpose model checker mCRL2. In order to make this familybased approach more scalable, the works [23,17] propose applying conservative variability abstractions on FTSs for deriving abstract family-based model checking of LTL.…”

Section: Related Workmentioning

confidence: 99%

Abstract Family-Based Model Checking Using Modal Featured Transition Systems: Preservation of CTL$$^{\star }$$⋆

Dimovski

2018

Fundamental Approaches to Software Engineering

View full text Add to dashboard Cite

Variational systems allow effective building of many custom variants by using features (configuration options) to mark the variable functionality. In many of the applications, their quality assurance and formal verification are of paramount importance. Family-based model checking allows simultaneous verification of all variants of a variational system in a single run by exploiting the commonalities between the variants. Yet, its computational cost still greatly depends on the number of variants (often huge). In this work, we show how to achieve efficient family-based model checking of CTL temporal properties using variability abstractions and off-theshelf (single-system) tools. We use variability abstractions for deriving abstract family-based model checking, where the variability model of a variational system is replaced with an abstract (smaller) version of it, called modal featured transition system, which preserves the satisfaction of both universal and existential temporal properties, as expressible in CTL . Modal featured transition systems contain two kinds of transitions, termed may and must transitions, which are defined by the conservative (over-approximating) abstractions and their dual (under-approximating) abstractions, respectively. The variability abstractions can be combined with different partitionings of the set of variants to infer suitable divideand-conquer verification plans for the variational system. We illustrate the practicality of this approach for several variational systems.

show abstract

“…We consider a family of vending machines inspired by examples from the literature (e.g., [2,[6][7][8]15,28]). For illustration purposes, we consider a simple version.…”

Section: Qflan At Work: Coffee Vending Machinementioning

confidence: 99%

“…This led to so-called family-based analyses [32]: analyse properties on an entire product line and use variability knowledge about valid feature configurations to deduce results for individual products. This is applied in, e.g., [8,10,11,15,[19][20][21][22][23]28,30].…”

Section: Introductionmentioning

confidence: 99%

“…Next to dedicated exact model checkers such as VMC [6] and the tool suite ProVeLines [17], which offers the best known SPL-specific model checker, SNIP [12], also popular model checkers like mCRL2 and SPIN have been made amenable to SPL model checking [7,8,[19][20][21]. Furthermore, the tool ProFeat [11] extends the probabilistic model checker PRISM [24] with feature-oriented concepts to be able to model families of stochastic systems and to analyze them through probabilistic model checking.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

QFLan: A Tool for the Quantitative Analysis of Highly Reconfigurable Systems

Vandin¹,

Beek²,

Legay³

et al. 2018

EasyChair Preprints

Self Cite

View full text Add to dashboard Cite

Abstract. QFLan offers modeling and analysis of highly reconfigurable systems, like product lines, which are characterized by combinatorially many system variants (or products) that can be obtained via different combinations of installed features. The tool offers a modern integrated development environment for the homonym probabilistic feature-oriented language. QFLan allows the specification of a family of products in terms of a feature model with quantitative attributes, which defines the valid feature combinations, and probabilistic behavior subject to quantitative constraints. The language's behavioral part enables dynamic installation, removal and replacement of features. QFLan has a discrete-time Markov chain semantics, permitting quantitative analyses. Thanks to a seamless integration with the statistical model checker MultiVeStA, it allows for analyses like the likelihood of specific behavior or the expected average value of non-functional aspects related to feature attributes.

show abstract

Family-Based Model Checking with mCRL2

Cited by 34 publications

References 41 publications

The mCRL2 Toolset for Analysing Concurrent Systems

The mCRL2 Toolset for Analysing Concurrent Systems

Abstract Family-Based Model Checking Using Modal Featured Transition Systems: Preservation of CTL$$^{\star }$$⋆

QFLan: A Tool for the Quantitative Analysis of Highly Reconfigurable Systems

Contact Info

Product

Resources

About