Paper Info
Title
A framework for quantitative modeling and analysis of highly (re)configurable systems.
Abstract
This paper presents our approach to the quantitative modeling and analysis of highly (re)configurable systems, such as software product lines. Different combinations of the optional features of such a system give rise to combinatorially many individual system variants. We use a formal modeling language that allows us to model systems with probabilistic behavior, possibly subject to quantitative feature constraints, and able to dynamically install, remove or replace features. More precisely, our models are defined in the probabilistic feature-oriented language QFLAN, a rich domain specific language (DSL) for systems with variability defined in terms of features. QFLAN specifications are automatically encoded in terms of a process algebra whose operational behavior interacts with a store of constraints, and hence allows to separate system configuration from system behavior. The resulting probabilistic configurations and behavior converge seamlessly in a semantics based on discrete-time Markov chains, thus enabling quantitative analysis. Our analysis is based on statistical model checking techniques, which allow us to scale to larger models with respect to precise probabilistic analysis techniques. The analyses we can conduct range from the likelihood of specific behavior to the expected average cost, in terms of feature attributes, of specific system variants. Our approach is supported by a novel Eclipse-based tool which includes state-of-the-art DSL utilities for QFLAN based on the Xtext framework as well as analysis plug-ins to seamlessly run statistical model checking analyses. We provide a number of case studies that have driven and validated the development of our framework.
Year
DOI
Venue
2017
10.1109/tse.2018.2853726
IEEE Transactions on Software Engineering
Field
DocType
Volume
Domain-specific language,Data mining,Computer science,Markov chain,Modeling language,Probabilistic analysis of algorithms,Theoretical computer science,Software,Probabilistic logic,Process calculus,Semantics
Journal
abs/1707.08411
Citations 
PageRank 
References 
6
0.41
0
Authors
4
Name
Order
Citations
PageRank
Maurice H. ter Beek171862.08
Axel Legay22982181.47
Alberto Lluch-Lafuente370651.82
Andrea Vandin420121.36