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

Andrea Vandin, Maurice H. Ter Beek, Axel Legay, Alberto Lluch Lafuente

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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.
Original languageEnglish
Title of host publicationFormal Methods
EditorsKlaus Havelund , Jan Peleska , Bill Roscoe , Erik de Vink
Number of pages9
PublisherSpringer
Publication date2018
Pages329-337
ISBN (Print)978-3-319-95581-0
ISBN (Electronic)978-3-319-95582-7
DOIs
Publication statusPublished - 2018
EventFederated Logic Conference 2018 - Oxford, United Kingdom
Duration: 15 Jul 201817 Jul 2018

Conference

ConferenceFederated Logic Conference 2018
CountryUnited Kingdom
CityOxford
Period15/07/201817/07/2018
SeriesLecture Notes in Computer Science
Volume10951
ISSN0302-9743

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