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

Analysis, Test and Verification in The Presence of Variability (Dagstuhl Seminar 13091)

This report documents the program and the outcomes of Dagstuhl Seminar 13091 "Analysis, Test and Verification in The Presence of Variability". The seminar had the goal of consolidating and stimulating research on analysis of software models with variability, enabling the design of variability-aware tool chains. We brought together 46 key researchers from three continents, working on quality assurance challenges that arise from introducing variability, and some who do not work with variability, but that are experts in their respective areas in the broader domain of software analysis or testing research. As a result of interactions triggered by sessions of different formats, the participants were able to classify their approaches with respect to a number of dimensions that helped to identify similarities and differences that have already been useful to improve understanding and foster new collaborations among the participants