Long-term average cost in featured transition systems

Abstract

A software product line is a family of software products that share a common set of mandatory features and whose individual products are differentiated by their variable (optional or alternative) features. Family-based analysis of software product lines takes as input a single model of a complete product line and analyzes all its products at the same time.As the number of products in a software product line may be large, this is generally preferable to analyzing each product on its own. Family-based analysis, however, requires that standard algorithms be adapted to accomodate variability.In this paper we adapt the standard algorithm for computing limit average cost of a weighted transition system to software product lines. Limit average is a useful and popular measure for the long-term average behavior of a quality attribute such as performance or energy consumption, but has hitherto not been available for family-based analysis of software product lines. Our algorithm operates on weighted featured transition systems, at a symbolic level, and computes limit average cost for all products in a software product line at the same time. We have implemented the algorithm and evaluated it on several examples.

Featured Weighted Automata

“…is will enable feature-based treatment of properties such as limit-average cost and will be useful for an extension to the timed se ing of [7]. From a practical point of view, we have shown in [21] that efficient algorithms are available for the limitaverage se ing.…”

On Featured Transition Systems

“…First we would like to extend our verification algorithms to quantitative software product lines. This requires to extend the FTS formalism to specify quantities [31]. Another interesting information to specify in FTS is probabilities, in order to perform statistical model-checking activities [33].…”

Multifaceted Automated Analyses for Variability-Intensive Embedded Systems

“…It attempts to assess [6], [7] or efficiently predict [8]- [13] non-functional properties of the whole product line, thus tackling both FCS and NFS. Extensions of these methods with multi-objective optimization [14]- [19] allow to find optimal variants wrt. structural quality attributes, thereby solving NFOS.…”

“…Behavioural analyses of variable systems were addressed by variability-aware model checking against functional requirements (challenge FCB) [20]- [23] or one particular nonfunctional aspect (e.g. real time [24]- [26], reliability [27], [28], income [19], quality of service [29]). Resource-optimal execution [30]- [33] and worst-case execution time [34] are still determined product by product.…”

“…The other model checker is ProVeLines [77], which can check variability-intensive systems. We chose this tool because it was extended over the years, by both its original developers [77] and others [19], [29], to solve multiple modelchecking problems including real-time verification [24]. We fully implemented Alg.…”