Quantitative Analysis of Probabilistic Models of Software Product Lines with Statistical Model Checking

• Published in: Electronic proceedings in theoretical computer science Vol. 182; no. Proc. FMSPLE 2015; pp. 56 - 70
• Main Authors: ter Beek, Maurice H., Legay, Axel, Lluch Lafuente, Alberto, Vandin, Andrea
• Format: Journal Article
• Language: English
• Published: Open Publishing Association 12-04-2015
• ISSN: 2075-2180; 2075-2180
• DOI: 10.4204/EPTCS.182.5

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.