2017
DOI: 10.1007/978-3-662-54494-5_23
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Family-Based Model Checking with mCRL2

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Cited by 36 publications
(39 citation statements)
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“…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%
“…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%
“…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%
“…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%
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