A Propositional Logic-Based Method for Verification of Feature Models

Zhang, Wei; Zhao, Haiyan; Mei, Hong

doi:10.1007/978-3-540-30482-1_16

Cited by 58 publications

(40 citation statements)

References 13 publications

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“…For example, the MCS product line presented in section 2 can be specified, by using the rules presented in subsection A, with the following program. [2,8], [3,16], [4,32]], [Processor, InternalMemory]) ˄ relation([ [1,1], [2,2], [3,3], [4,3], [5,3], [6 ,4], [7,4], [8,4] Figure 3 illustrates the constraints set specifying the MCS example and their interdependencies. Any constraint solver can be then used to solve the program.…”

Section: B Example Illustrationmentioning

confidence: 99%

“…Some proposals had been made to support automatic analysis of feature-based models in order to allow retrieving information. The largest number of works to automate features analysis is based on propositional logic [1,2,3,18].…”

Section: Related Workmentioning

confidence: 99%

“…Propositional logic has been used to deal with Product Line Engineering (PLE) [1,2,3,5]. More recent works [4,6,28,29] show the interest of the international community of PLE to represent and analyze Product Line (PL) models by using constraint programming.…”

Section: Introductionmentioning

confidence: 99%

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Constraints: The core of product line engineering

Salinesi

Mazo

Djebbi

et al. 2011

2011 Fifth International Conference on Research Challenges in Information Science

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Abstract-Product line engineering is a reuse-driven development paradigm based on the management of variability, which was successfully applied in information systems engineering and other domains. A common way to represent variability is with variability models that describe artefacts, and the dependencies between their various inflexions. Constraint programming, and in particular Boolean constraint programming, has been used so far to support analysis of variability models such as Feature-Oriented Domain Analysis (FODA) and the like. This paper goes a step further by using constraint programming to specify product lines. The focus on variability, variation points or dependencies is switched to the concept of constraints that apply to variables. The paper shows that this approach is richer than the one based on dependencies. For instance, many constraints that were needed in the cases we explored cannot be specified with dependencies of existing product line modelling languages. The approach was implemented in a prototype tool, and its scalability explored with industry case studies. These experiments show that constraint programming encompasses existing product line modelling languages such as FODA or OVM (Orthogonal Variability Model) and opens way to new possibilities such as reasoning simultaneously with different models during domain or application engineering.

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Section: B Example Illustrationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Constraints: The core of product line engineering

Salinesi

Mazo

Djebbi

et al. 2011

2011 Fifth International Conference on Research Challenges in Information Science

View full text Add to dashboard Cite

show abstract

“…var 1 (i) ⇒ var 2 (i) ∧ ¬var 3 (i) for instance i) can be per-formed [30]. Feature models defined with differing degrees of genericity, binding into the software construction process at different points, can be validated similarly [46]. Formal models also allow formal verification to happen, e.g.…”

Section: Related Work In Contextmentioning

confidence: 99%

“…Formal models also allow formal verification to happen, e.g. feature modelchecking [46] and product line architectural model-checking for commonalities of robustness and fault-tolerance [28].…”

Section: Related Work In Contextmentioning

confidence: 99%

Rigorous engineering of product-line requirements: A case study in failure management

Snook

Poppleton

Johnson³

2008

Information and Software Technology

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We consider the failure detection and management function for engine control systems as an application domain where product line engineering is indicated. The need to develop a generic requirement set -for subsequent system instantiation -is complicated by the addition of the high levels of verification demanded by this safety-critical domain, subject to avionics industry standards. We present our case study experience in this area as a candidate method for the engineering, validation and verification of generic requirements using domain engineering and Formal Methods techniques and tools. For a defined class of systems, the case study produces a generic requirement set in UML and an example system instance. Domain analysis and engineering produce a validated model which is integrated with the formal specification/ verification method B by the use of our UML-B profile. The formal verification both of the generic requirement set, and of a simple system instance, is demonstrated using our U2B, ProB and prototype Requirements Manager tools. This work is a demonstrator for a tool-supported method which will be an output of EU project RODIN 1 . The use of existing and prototype formal verification and support tools is discussed. The method, developed in application to this novel combination of product line, failure management and safety-critical engineering, is evaluated and considered to be applicable to a wide range of domains.

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Formalizing cardinality‐based feature models and their specialization

Czarnecki

Helsen

Eisenecker

2005

Softw Process Imprv Pract

428

265

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Feature modeling is an important approach to capture the commonalities and variabilities in system families and product lines. Cardinality‐based feature modeling integrates a number of existing extensions of the original feature‐modeling notation from Feature‐Oriented Domain Analysis. Staged configuration is a process that allows the incremental configuration of cardinality‐based feature models. It can be achieved by performing a step‐wise specialization of the feature model. In this article, we argue that cardinality‐based feature models can be interpreted as a special class of context‐free grammars. We make this precise by specifying a translation from a feature model into a context‐free grammar. Consequently, we provide a semantic interpretation for cardinality‐based feature models by assigning an appropriate semantics to the language recognized by the corresponding grammar. Finally, we give an account on how feature model specialization can be formalized as transformations on the grammar equivalent of feature models. Copyright © 2005 John Wiley & Sons, Ltd.

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A Propositional Logic-Based Method for Verification of Feature Models

Cited by 58 publications

References 13 publications

Constraints: The core of product line engineering

Constraints: The core of product line engineering

Rigorous engineering of product-line requirements: A case study in failure management

Formalizing cardinality‐based feature models and their specialization

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