Paper Info
Title
Statistical Model Checking for Product Lines.
Abstract
We report on the suitability of statistical model checking for the analysis of quantitative properties of product line models by an extended treatment of earlier work by the authors. The type of analysis that can be performed includes the likelihood of specific product behaviour, the expected average cost of products (in terms of the attributes of the products' features) and the probability of features to be (un) installed at runtime. The product lines must be modelled in QFLan, which extends the probabilistic feature-oriented language PFLan with novel quantitative constraints among features and on behaviour and with advanced feature installation options. QFLan is a rich process-algebraic specification language whose operational behaviour interacts with a store of constraints, neatly separating product configuration from product behaviour. The resulting probabilistic configurations and probabilistic behaviour converge in a discrete-time Markov chain semantics, enabling the analysis of quantitative properties. Technically, a Maude implementation of QFLan, integrated with Microsoft's SMT constraint solver Z3, is combined with the distributed statistical model checker MultiVeStA, developed by one of the authors. We illustrate the feasibility of our framework by applying it to a case study of a product line of bikes.
Year
DOI
Venue
2016
10.1007/978-3-319-47166-2_8
Lecture Notes in Computer Science
Field
DocType
Volume
Specification language,Programming language,Computer science,Markov chain,Theoretical computer science,Average cost,Constraint satisfaction problem,Statistical model,Software product line,Probabilistic logic,Semantics
Conference
9952
ISSN
Citations 
PageRank 
0302-9743
9
0.45
References 
Authors
28
4
Name
Order
Citations
PageRank
Maurice H. ter Beek171862.08
Axel Legay22982181.47
Alberto Lluch-Lafuente370651.82
Andrea Vandin420121.36