Andrzej Wąsowski

Modal I/O automata for interface and product line theories

Alfaro and Henzinger use alternating simulation in a two player game as a refinement for interface automata [1]. We show that interface automata correspond to a subset of modal transition systems of Larsen and Thomsen [2], on which alternating simulation coincides with modal refinement. As a consequence a more expressive interface theory may be built, by a simple generalization from interface automata to modal automata. We define modal I/O automata, an extension of interface automata with modality. Our interface theory that follows can express liveness properties, disallowing trivial implementations of interfaces, a problem that exists for theories build around simulation preorders. In order to further exemplify the usefulness of modal I/O automata, we construct a behavioral variability theory for product line development.

Cool features and tough decisions: a comparison of variability modeling approaches

Variability modeling is essential for defining and managing the commonalities and variabilities in software product lines. Numerous variability modeling approaches exist today to support domain and application engineering activities. Most are based on feature modeling (FM) or decision modeling (DM), but so far no systematic comparison exists between these two classes of approaches. Over the last two decades many new features have been added to both FM and DM and it is tough to decide which approach to use for what purpose. This paper clarifies the relation between FM and DM. We aim to systematize the research field of variability modeling and to explore potential synergies. We compare multiple aspects of FM and DM ranging from historical origins and rationale, through syntactic and semantic richness, to tool support, identifying commonalities and differences. We hope that this effort will improve the understanding of the range of approaches to variability modeling by discussing the possible variations. This will provide insights to users considering adopting variability modeling in practice and to designers of new languages, such as the new OMG Common Variability Language.

A survey of variability modeling in industrial practice

Over more than two decades, numerous variability modeling techniques have been introduced in academia and industry. However, little is known about the actual use of these techniques. While dozens of experience reports on software product line engineering exist, only very few focus on variability modeling. This lack of empirical data threatens the validity of existing techniques, and hinders their improvement. As part of our effort to improve empirical understanding of variability modeling, we present the results of a survey questionnaire distributed to industrial practitioners. These results provide insights into application scenarios and perceived benefits of variability modeling, the notations and tools used, the scale of industrial models, and experienced challenges and mitigation strategies.

Variability modeling in the real: a perspective from the operating systems domain

Variability models represent the common and variable features of products in a product line. Several variability modeling languages have been proposed in academia and industry; however, little is known about the practical use of such languages. We study and compare the constructs, semantics, usage and tools of two variability modeling languages, Kconfig and CDL. We provide empirical evidence for the real-world use of the concepts known from variability modeling research. Since variability models provide basis for automated tools (feature dependency checkers and product configurators), we believe that our findings will be of interest to variability modeling language and tool designers.

Evolution of the linux kernel variability model

Understanding the challenges faced by real projects in evolving variability models, is a prerequisite for providing adequate support for such undertakings. We study the evolution of a model describing features and configurations in a large product line--the Linux kernel variability model. We analyze this evolution quantitatively and qualitatively. Our primary finding is that the Linux kernel model appears to evolve surprisingly smoothly. In the analyzed period, the number of features had doubled, and still the structural complexity of the model remained roughly the same. Furthermore, we provide an in-depth look at the effect of the kernels development methodologies on the evolution of its model. We also include evidence about edit operations applied in practice, evidence of challenges in maintaining large models, and a range of recommendations (and open problems) for builders of modeling tools.

Moving from specifications to contracts in component-based design

We study the relation between specifications of component behaviors and contracts providing means to specify assumptions on environments as well as component guarantees. We show how a contract framework can be built in a generic way on top of any specification theory which supports composition and specification refinement. Our contract framework lifts refinement to the level of contracts and proposes a notion of contract composition on the basis of dominating contracts. Contract composition satisfies a universal property and can be constructively defined if the underlying specification theory is complete, i.e. it offers operators for quotienting and conjoining specifications. We illustrate our generic construction of contracts by moving a specification theory for modal transition systems to contracts and we show that a (previously proposed) trace-based contract theory is an instance of our framework.

A Modal Specification Theory for Components with Data

Modal specification is a well-known formalism used as an abstraction theory for transition systems. Modal specifications are transition systems equipped with two types of transitions: must-transitions that are mandatory to any implementation, and may-transitions that are optional. The duality of transitions allows to develop a unique approach for both logical and structural compositions, and eases the step-wise refinement process for building implementations.

Constraint Markov chains

Notions of specification, implementation, satisfaction, and refinement, together with operators supporting stepwise design, constitute a specification theory. We construct such a theory for Markov Chains (MCs) employing a new abstraction of a Constraint MC. Constraint MCs permit rich constraints on probability distributions and thus generalize prior abstractions such as Interval MCs. Linear (polynomial) constraints suffice for closure under conjunction (respectively parallel composition). This is the first specification theory for MCs with such closure properties. We discuss its relation to simpler operators for known languages such as probabilistic process algebra. Despite the generality, all operators and relations are computable.

Efficient synthesis of feature models

Variability modeling, and in particular feature modeling, is a central element of model-driven software product line architectures. Such architectures often emerge from legacy code, but, unfortunately creating feature models from large, legacy systems is a long and arduous task. We address the problem of automatic synthesis of feature models from propositional constraints. We show that this problem is NP-hard. We design efficient techniques for synthesis of models from respectively CNF and DNF formulas, showing a 10- to 1000-fold performance improvement over known techniques for realistic benchmarks. Our algorithms are the first known techniques that are efficient enough to be applied to dependencies extracted from real systems, opening new possibilities of creating reverse engineering and model management tools for variability models. We discuss several such scenarios in the paper.

Flexible product line engineering with a virtual platform

Cloning is widely used for creating new product variants. While it has low adoption costs, it often leads to maintenance problems. Long term reliance on cloning is discouraged in favor of systematic reuse offered by product line engineering (PLE) with a central platform integrating all reusable assets. Unfortunately, adopting an integrated platform requires a risky and costly migration. However, industrial experience shows that some benefits of an integrated platform can be achieved by properly managing a set of cloned variants. In this paper, we propose an incremental and minimally invasive PLE adoption strategy called virtual platform. Virtual platform covers a spectrum of strategies between ad-hoc clone and own and PLE with a fully-integrated platform divided into six governance levels. Transitioning to a governance level requires some effort and it provides some incremental benefits. We discuss tradeoffs among the levels and illustrate the strategy on an example implementation.