PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Ter Beek M. H., Legay A., Lluch Lafuente A., Vandin A. Quantitative analysis of probabilistic models of software product lines with statistical model checking. In: FMSPLE'15 - 6th International Workshop on Formal Methods for Software Product Line Engineering (London, UK, 11 April 2015). Proceedings, pp. 56 - 70. J.M. Atlee, S. Gnesi (eds.). (Electronic Proceedings in Theoretical Computer Science, vol. 182). EPTCS, 2015.
 
 
Abstract
(English)
We investigate the suitability of statistical model checking techniques for analysing quantitative properties of software product line models with probabilistic aspects. For this purpose, we enrich the feature-oriented language FLan with action rates, which specify the likelihood of exhibiting particular behaviour or of installing features at a specific moment or in a specific order. The enriched language (called PFLan) allows us to specify models of software product lines with probabilistic configurations and behaviour, e.g. by considering a PFLan semantics based on discrete-time Markov chains. The Maude implementation of PFLan is combined with the distributed statistical model checker MultiVeStA to perform quantitative analyses of a simple product line case study. The presented analyses include the likelihood of certain behaviour of interest (e.g. product malfunctioning) and the expected average cost of products.
URL: http://eptcs.web.cse.unsw.edu.au/paper.cgi?FMSPLE15.5
DOI: 10.4204/EPTCS.182.5
Subject Software Product Lines
Probabilistic Models
Quantitative Analysis
Statistical Model Checking
Process Algebra
Maude
MultiVeStA
D.2.4 Software/Program Verification. Formal Methods
D.2.4 Software/Program Verification. Model checking
F.3.1 Specifying and Verifying and Reasoning about Programs
F.3.2 Semantics of Programming Languages
G.3 Probability and Statistics


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