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

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.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301

Using FMC for family-based analysis of software product lines

We show how the FMC model checker can successfully be used to model and analyze behavioural variability in Soft-ware Product Lines. FMC accepts parameterized specifi-cations in a process-algebraic input language and allows the verification of properties of such models by means of efficient on-the-fly model checking. The properties can be expressed in a logic that allows to correlate the parameters of different actions within the same formula. We show how this feature can be used to tailor formulas to the verification of only a specific subset of products of a Software Product Line, thus allowing for scalable family-based analyses with FMC. We present a proof-of-concept that shows the application of FMC to an illustrative Featured Transition System from the literature. CCS Concepts •General and reference → Verification; •Theory of computation→Verification by model checking; Modal and temporal logics; Process calculi; Operational semantics; •Software and its engineering → Model checking; Software product lines; Model-driven software engineer-ing

Software product line analysis with mCRL2

The mCRL2 language and supporting software provide a state-of-the-art tool suite for the verification of distributed systems. In this paper, we present the general principles, extrapolated from [7,8], which make us believe that mCRL2 can also be used for behavioral variability analysis of product families. The mCRL2 data language allows to smoothly deal with feature sets and attributes, its process language is sufficiently rich to model feature selection, as well as product behavior based on an FTS-like semantics. Because of the feature-orientation, our modeling strategy allows a natural refactoring of the semantic model of a product family into a parallel composition of components that reflects coherent sets of features. This opens the way for dedicated abstraction and reduction techniques that strengthen the prospect of a scalable verification approach to software product lines. In this paper, we sketch how to model product families in mCRL2 and how to apply a modular verification method, preparing the ground to further assess the scalability of our approach, in particular regarding model checking. Keywords: Product families, Variability, Behavioral analysis, Modular verification, Model checkin