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Feature Nets: behavioural modelling of software product lines

Title
Feature Nets: behavioural modelling of software product lines
Type
Article in International Scientific Journal
Year
2016
Authors
Muschevici, R
(Author)
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Proenca, J
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Clarke, D
(Author)
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Journal
The Journal is awaiting validation by the Administrative Services.
Vol. 15
Pages: 1181-1206
ISSN: 1619-1366
Other information
Authenticus ID: P-00G-BTX
Abstract (EN): Software product lines (SPLs) are diverse systems that are developed using a dual engineering process: (a) family engineering defines the commonality and variability among all members of the SPL, and (b) application engineering derives specific products based on the common foundation combined with a variable selection of features. The number of derivable products in an SPL can thus be exponential in the number of features. This inherent complexity poses two main challenges when it comes to modelling: firstly, the formalism used for modelling SPLs needs to be modular and scalable. Secondly, it should ensure that all products behave correctly by providing the ability to analyse and verify complex models efficiently. In this paper, we propose to integrate an established modelling formalism (Petri nets) with the domain of software product line engineering. To this end, we extend Petri nets to Feature Nets. While Petri nets provide a framework for formally modelling and verifying single software systems, Feature Nets offer the same sort of benefits for software product lines. We show how SPLs can be modelled in an incremental, modular fashion using Feature Nets, provide a Feature Nets variant that supports modelling dynamic SPLs, and propose an analysis method for SPL modelled as Feature Nets. By facilitating the construction of a single model that includes the various behaviours exhibited by the products in an SPL, we make a significant step towards efficient and practical quality assurance methods for software product lines.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 26
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