Search

A product line is an approach for systematically managing configuration options of customizable systems, usually by means of features. Products are generated for configurations consisting of selected features. Product-line evolution can lead to unintended changes to product behavior. We illustrate that updating configurations after product-line evolution requires decisions of both, domain engineers responsible for product-line evolution as well as application engineers responsible for configurations. The challenge is that domain and application engineers might not be able to interact with each other. We propose a formal foundation and a methodology that enables domain engineers to guide application engineers through configuration evolution by sharing knowledge on product-line evolution and by defining automatic update operations for configurations. As an effect, we enable knowledge transfer between those engineers without the need for interactions. We evaluate our methodology on four large-scale industrial product lines. The results of the qualitative evaluation indicate that our method is flexible enough for real-world product-line evolution. The quantitative evaluation indicates that we detect product behavior changes for up to 55.3%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$55.3\%$$\end{document} of the configurations which would not have been detected using existing methods., publishedVersion

Modelling is an essential activity in software engineering. Ittypically involves two meta-levels: one includes meta-models thatdescribe modelling languages, and the other contains models built byinstantiating those meta-models. Multi-level modelling generalizes this approach by allowing models to span an arbitrarynumber of meta-levels. A scenario that profits from multi-levelmodelling is the definition of language families that can bespecialized (e.g., for different domains) by successive refinementsat subsequent meta-levels, hence promoting language reuse. Thisenables an open set of variability options given by allpossible specializations of the language family. However,multi-level modelling lacks the ability to express closed variability regarding the availability of language primitives or thepossibility to opt between alternative primitive realizations. Thislimits the reuse opportunities of a language family. To improve thissituation, we propose a novel combination of product lines withmulti-level modelling to cover both open and closed variability. Ourproposal is backed by a formal theory that guarantees correctness,enables top-down and bottom-up language variability design, and isimplemented atop the MetaDepth multi-level modelling tool, This work has been funded by the SpanishMinistry of Science (project MASSIVE, RTI2018-095255- B-I00), by the R&D programme of Madrid (project FORTE, P2018/TCS-4314), and the Universidad Autónoma de Madrid

Modelling is an essential activity in software engineering processes. It typically involves two meta-levels: one includes meta-models that describe modelling languages, and the other contains models built by instantiating those meta-models. Multi-level modelling generalizes this approach by allowing models to span an arbitrary number of meta-levels. A scenario that profits from multi-level modelling is the definition of language families that become specialized by successive refinements at subsequent meta-levels, hence promoting language reuse. This enables an open set of variability options for the possible specializations of a given language. However, multi-level modelling lacks the ability to express closed variability regarding the supported language primitives and their realizations. This limits the reuse opportunities of a language family. To improve this situation, we propose a novel combination of product lines with multi-level modelling to cover both open and closed variability. Our proposal is backed by a formal theory that guarantees correctness, and is implemented atop the MetaDepth multi-level modelling tool., Work funded by the Spanish Ministry of Science (project MASSIVE, RTI2018-095255-B-I00) and the R&D programme of Madrid (project FORTE, P2018/TCS-4314).

This thesis handles fundamental problems faced by retailers everyday: how do consumers make choices from an enormous variety of products? How to design a product portfolio to maximize the expected profit given consumers’ choice behavior? How to frame products if consumers’ choices are influenced by the display location? We solve those problems by first, constructing mathematical models to describe consumers’ choice behavior from a given offer set, i.e., consumer choice models; second, by designing efficient algorithms to optimally select the product portfolio to maximize the expected profit, i.e., assortment optimization. This thesis consists of three main parts: the first part solves assortment optimization problem under a consideration set based choice model proposed by Manzini and Mariotti (2014) [Manzini, Paola, Marco Mariotti. 2014. Stochastic choice and consideration sets. Econometrica 82(3) 1153-1176.]; the second part proposes an approximation algorithm to jointly optimize products’ selection and display; the third part works on optimally designing a product line under the Logit family choice models when a product’s utility depends on attribute-level configurations.

Many modern software-intensive systems consist of multiple components interacting together to deliver the intended functionality. Often, these systems come in many variants (products) and are managed together as a software product line. This variability is the source of additional complexity which can cause inconsistencies and offset the economies of scale promised by product line engineering. Engineers thus need intuitive, yet precise means for specifying requirements and require tools for automatically detecting inconsistencies within these requirements. In recent work, we proposed a technique for the scenario-based specification of interactions in product lines by a combination of Modal Sequence Diagrams and Feature Diagrams. Furthermore, we elaborated an efficient consistency-checking technique based on a dedicated model-checking approach especially tailored for product lines. In this paper, we report on further evaluations that underline significant performance benefits of our approach. We describe further optimizations and detail on how we encode the consistency-checking problem for a model-checker.

Context. A Feature Model (FM) represents the valid combinations of features in a domain. The automated extraction of information from FMs is a complex task that involves numerous analysis operations, techniques and tools. Current testing methods in this context are manual and rely on the ability of the tester to decide whether the output of an analysis is correct. However, this is acknowledged to be timeconsuming, error-prone and in most cases infeasible due to the combinatorial complexity of the analyses, this is known as the oracle problem. Objective. In this paper, we propose using metamorphic testing to automate the generation of test data for feature model analysis tools overcoming the oracle problem. An automated test data generator is presented and evaluated to show the feasibility of our approach. Method. We present a set of relations (so-called metamorphic relations) between input FMs and the set of products they represent. Based on these relations and given a FM and its known set of products, a set of neighbouring FMs together with their corresponding set of products are automatically generated and used for testing multiple analyses. Complex FMs representing millions of products can be efficiently created by applying this process iteratively. Results. Our evaluation results using mutation testing and real faults reveal that most faults can be automatically detected within a few seconds. Two defects were found in FaMa and another two in SPLOT, two real tools for the automated analysis of feature models. Also, we show how our generator outperforms a related manual suite for the automated analysis of feature models and how this suite can be used to guide the automated generation of test cases obtaining important gains in efficiency. Conclusion. Our results show that the application of metamorphic testing in the domain of automated analysis of feature models is efficient and effective in detecting most faults in a few seconds without the need for the human oracle. CICYT SETI TIN2009-07366 Junta de Andalucía ISABEL TIC-2533

Model-driven development envisions raising the abstraction level of software development. To fully realize this vision, technology-specific aspects must be completely hidden from developers. They produce only platform-independent models (PIM), which are automatically transformed into executable systems. To enable an efficient migration to MDD, we recommend taking advantage of concepts from software architectures, product line engineering and reverse engineering.

Software systems could be seen as a hierarchy of features which are evolving due to the dynamic of the working environments. The companies who build software thus need to make an appropriate strategy, which takes into consideration of such dynamic, to select features to be implemented. In this work, we propose an approach to facilitate such selection by providing a means to capture the uncertainty of evolution in feature models. We also provide two analyses to support the decision makers. The approach is exemplified in the Smart Grid scenario.

Part 22: Sustainable Collaborative Networks III; International audience; To cope with the customer-oriented business model in a global competitive market, enterprises tend to be networked for achieving mass customisation: i.e. offering customisable products with the same efficiency as mass production. This scenario highlights two faces of variability: variability of needs (on customer side) and variability of organisations (on production side). Both types of variability induce a huge number of specified products, namely configurations. This configuration variability must be efficiently managed. This position paper discusses trends and issues for rationalising the number of configurations: i.e. engineering the right number of configurations that match both the customer needs and the production strategy. After this positioning, we propose a systemic perspective for addressing the discussed issues from a sustainability point of view. Finally we give a perspective for a product line definition method that leads to models that meet the discussed variability rationalisation.

peer-reviewed Access control systems are deployed in organizations to protect critical cyber-physical assets. These systems need to be adjustable to cope with di erent contextual factors like changes in resources or requirements. Still, adaptation is often performed manually. In addition, di erent product variants of access control systems need to developed together systematically. These characteristics demand a product line engineering approach for enhanced reuse. Moreover, to cope with uncertainty at runtime, adaptivity, i.e., switching between variations in a cyber-physical domain (recon guration) and adjusting access policies (behavior adaptation), needs to be supported. In this position paper, we sketch an approach for engineering dynamic access control systems based on core concepts from dynamic software product lines and executable runtime models. The proposed solution is presented and rst experiences are discussed along a sample dynamic software product line in the role-based access control domain.

PL for SOA proposes, formally, a software engineering methodology, development techniques and support tools for the provision of service product lines. We propose rigorous modeling techniques for the specification and verification of formal notations and languages for service computing with inclinations of variability. Through these cutting-edge technologies, increased levels of flexibility and adaptivity can be achieved. This will involve developing semantics of variability over behavioural models of services. Such tools will assist organizations to plan, optimize and control the quality of software service provision, both at design and at run time by making it possible to develop flexible and cost-effective software systems that support high levels of reuse. We tackle this challenge from two levels. We use feature modeling from product line engineering and, from a services point of view, the orchestration language Orc. We introduce the Smart Grid as the service product line to apply the techniques to., Comment: In Proceedings WWV 2011, arXiv:1108.2085

International audience; The current technology gives little room for the different kinds of evolution needed for any software product line (SPL): evolution of the associated engineering environment, evolution of the market and SPL scope, evolution of the products and variability. The paper describes how these different evolution needs are addressed in the CADSE and Selecta systems. The solution we propose uses metamodeling and generation for the engineering environment evolution, composition for scope and market evolution, a component database and a selection language for the product and variability evolution. The paper presents the Selecta system and shortly discusses the experience.

In this paper we propose a behavioural model, namely the Generalized Extended Modal Transition Systems, as a basis for the formalization of different notions of variability usually present in product families definitions. In particular, a GEMTS is able to define a family of products by telling at any state of the system whether some (and how many) transitions are optional or mandatory for any derived products of the family. The proposed model is compared with previous proposals also based on Labeled Transition Systems, showing its higher generality, but also pointing out weaknesses that still need to be addressed with more expressive models. Hints on the solution of such weaknesses are given by the use of constraints expressed as temporal logic formulae.

The Paper addresses the issue of coordinated effects of mergers in the framework of a differentiated products model. Firms’ assets are product varieties that can be sold individually or entirely transferred to another firm in a merger. We show that under symmetric optimal punishment schemes the highest feasible collusive price declines from any asset transfer to the largest firm as long as the size of the smallest firm is unchanged. In contrast, for fully optimal punishment schemes the prices of firms that get larger increase and those of firms that get smaller decrease. In all cases, however, mergers are unprofitable unless the length of product lines is very asymmetric. We discuss the implications of the analysis for merger policy.

International audience; In the context of Product lines, the collaborative configuration process gets complicated when the configuration decisions of involved stakeholders are contradictory, which may lead to conflicting situations. Although considerable research has been devoted to collaborative configuration, little attention has been paid to conflict resolution. Moreover, most of existing approaches rely on a systematic process which constraint decisions of some stakeholders. In this paper, we propose a new collaborative configuration approach which allows conflict resolution based on stakeholders preferences expressed through a set of substitution rules. Based on such preferences, we delete the minimal set of conflicting configuration decisions which are identified using the Minimal Correction Subsets (MCSs) computing algorithm. An illustrating example and a tool prototype are presented to evaluate the applicability of our approach.

The objective of this workshop is to bring together researchers from the software product line community and software architecture community to identify critical challenges and progress the state-of-the-art on variability in software product line architectures.

International audience; Several formalisms can be used to express variability in a product line. Product comparison matrix is a common and simple way to display variability of existing products from a same family, but they lack of formalisation. In this paper, we focus on concept lattices, another alternative already explored in several works to express variability. We first propose a method to translate a description from existing product comparison matrices into a concept lattice using Formal Concept Analysis. Then, we propose an approach to represent the case where a product family is described by other product families with interconnected lattices using Relational Concept Analysis. Because of the combinatorial aspect of these approaches, we evaluate the scalability of the produced structures. We show that a particular structure (AOC-poset) possesses interesting properties for the studies that we envision.