A formal model for Multi Software Product Lines

Damiani, Ferruccio; Lienhardt, Michael; Paolini, Luca

doi:10.1016/j.scico.2018.11.005

Cited by 9 publications

(18 citation statements)

References 36 publications

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“…A program signature PS is an interface of program P, denoted as PS P, iff PS signature(P) holds. The notion of SPL signature (SPLS) [19] describes the API of an SPL, i.e., the APIs of the variants generated by the SPL. Namely, an SPLS is an SPL where the variants are program signatures instead of programs.…”

Section: Definition 6 (Interface Relation Between Signatures and Programs)mentioning

confidence: 99%

“…A delta-oriented SPLS [19] can be understood as a delta-oriented SPL where the variants are program signatures. The abstract syntax of the artifact base of an IF∆J SPLSs [19], called artifact base signature, is given in Figure 5.…”

Section: Delta-oriented Splss Of Ifj Programsmentioning

confidence: 99%

“…In this paper we formalize, by abstracting from SPL implementation approaches, the problem of designing an efficient algorithm that, given an SPL and subset F of it features, extracts an interface for the SPL that exposes only the functionalities associated to the features in F . We build on the notions of signature and interface of an SPL introduced in [17] (see also [19]). An SPL Signature (SPLS) is a variability-aware Application Programming Interface (API), i.e., an SPL where each variant is a program API.…”

Section: Introductionmentioning

confidence: 99%

“…2. We introduce and formalize the problem of devising a feasible algorithm that takes as input a delta-oriented SPLS Z [19] and a set of features F, and yields as output a delta-oriented SPLS that is a slice of Z for F. Thus paving the way for further research on devising such an algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Since extracting the signature of a delta-oriented SPL is quite straightforward [17], an algorithm like the one described in point 2 above would provide a way to extract from an SPL an interface that exposes only the functionalities associated to a given set of features. This would enable refactoring a delta-oriented SPL by decomposing it into a Multi SPL (MPL), that is a set of interdependent SPLs that need to be managed in a decentralized fashion by multiple teams and stakeholders [29], and performing compositional analysis of delta-oriented MPLs [19]. Moreover, the implementation-independent formalization described in point 1 above might foster further research on MPLs comprising SPLs implemented according to different approaches (see, e.g., [42,47,3] for a presentation of different SPL implementation approaches).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

On Slicing Software Product Line Signatures

Damiani

Lienhardt

Paolini

2020

Leveraging Applications of Formal Methods, Verification and Validation: Verification Principles

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A Software Product Line (SPL) is a family of similar programs (called variants) generated from a common artifact base. Variability in an SPL can be documented in terms of abstract description of functionalities (called features): a feature model (FM) identifies each variant by a set of features (called a product). Delta-orientation is a flexible approach to implement SPLs. An SPL Signature (SPLS) is a variability-aware Application Programming Interface (API), i.e., an SPL where each variant is the API of a program. In this paper we introduce and formalize, by abstracting from SPL implementation approaches, the notion of slice of an SPLS K for a set of features F (i.e., an SPLS obtained from by K by hiding the features that are not in F). Moreover, we formulate the challenge of defining an efficient algorithm that, given a delta-oriented SPLS K and a set of features F, returns a delta-oriented SPLS that is an slice of K for F. Thus paving the way for further research on devising such an algorithm. The proposed notions are formalized for SPLs of programs written in an imperative version of Featherweight Java.

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Section: Definition 6 (Interface Relation Between Signatures and Programs)mentioning

confidence: 99%

Section: Delta-oriented Splss Of Ifj Programsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

On Slicing Software Product Line Signatures

Damiani

Lienhardt

Paolini

2020

Leveraging Applications of Formal Methods, Verification and Validation: Verification Principles

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On Two Characterizations of Feature Models

Damiani

Lienhardt

Paolini

2020

Theoretical Aspects of Computing – ICTAC 2020

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Software-intensive systems can have thousands of interdependent configuration options across different subsystems. Feature models allow designers to organize the configuration space by describing configuration options using interdependent features: a feature is a name representing some functionality and each software variant is identified by set of features. Different representations of feature models have been proposed in the literature. In this paper we focus on the propositional representation (which works well in practice) and the extensional representation (which has been recently shown well suited for theoretical investigations). We provide an algebraic and a propositional characterization of novel and existing feature model operations and relations, and we formalize the connection between the two characterizations as monomorphisms from lattices of propositional feature models to lattices of extensional features models. These results shed new light on the correspondence between the extensional and the propositional representations of feature models. Thus paving the way towards facilitating practical exploitation, by relying on the propositional representation, of theoretical developments expressed by relying on the extensional representation.

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Efficient static analysis and verification of featured transition systems

et al. 2021

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A Featured Transition System (FTS) models the behaviour of all products of a Software Product Line (SPL) in a single compact structure, by associating action-labelled transitions with features that condition their presence in product behaviour. It may however be the case that the resulting featured transitions of an FTS cannot be executed in any product (so called dead transitions) or, on the contrary, can be executed in all products (so called false optional transitions). Moreover, an FTS may contain states from which a transition can be executed only in some products (so called hidden deadlock states). It is useful to detect such ambiguities and signal them to the modeller, because dead transitions indicate an anomaly in the FTS that must be corrected, false optional transitions indicate a redundancy that may be removed, and hidden deadlocks should be made explicit in the FTS to improve the understanding of the model and to enable efficient verification—if the deadlocks in the products should not be remedied in the first place. We provide an algorithm to analyse an FTS for ambiguities and a means to transform an ambiguous FTS into an unambiguous one. The scope is twofold: an ambiguous model is typically undesired as it gives an unclear idea of the SPL and, moreover, an unambiguous FTS can efficiently be model checked. We empirically show the suitability of the algorithm by applying it to a number of benchmark SPL examples from the literature, and we show how this facilitates a kind of family-based model checking of a wide range of properties on FTSs.

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A formal model for Multi Software Product Lines

Cited by 9 publications

References 36 publications

On Slicing Software Product Line Signatures

On Slicing Software Product Line Signatures

On Two Characterizations of Feature Models

Efficient static analysis and verification of featured transition systems

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