Feature Model Differences

International audienceFeature models are a widespread means to represent commonality and variability in software product lines. As is the case for other kinds of models, computing and managing feature model differences is useful in various real-world situations. In this paper, we propose a set of novel differencing techniques that combine syntactic and semantic mechanisms, and automatically produce meaningful differences. Practitioners can exploit our results in various ways: to understand, manipulate, visualize and reason about differences. They can also combine them with existing feature model composition and decomposition operators. The proposed automations rely on satisfiability algorithms. They come with a dedicated language and a comprehensive environment. We illustrate and evaluate the practical usage of our techniques through a case study dealing with a configurable component framework

Weaving Variability into Domain Metamodels

International audienceDomain-Specific Modeling Languages (DSMLs) describe the concepts of a particular domain and their relationships, in a meta-model. From a given DSML, it is possible to describe a wide range of different models. These models often share a common base and vary on some parts. Current approaches tend to distinguish the variability language from the DSMLs themselves, implying greater learning curve for DSMLs stakeholders and a significant overhead in product line engineering of DSLs. We propose to consider variability concepts as an independent aspect to be woven into the DSML to introduce variability capabilities. In particular we detail how variability is woven and how to perform product line derivation. We validate our approach through the weaving of variability into two very different metamodels: Ecore and SmartAdapter, our aspect-oriented modelling weaver, thus adding exibility in the weaving process itself. These results emphasize how new abilities of the language can be provided by this means

Carrying Ideas from Knowledge-Based Configuration to Software Product Lines

Software variability modelling (SVM) has become a central concern in software product lines -- especially configurable software product lines (CSPL) require rigorous SVM. Dynamic SPLs, service oriented SPLs, and autonomous or pervasive systems are examples where CSPLs are applied. Knowledge-based configuration (KBC) is an established way to address variability modelling aiming for the automatic product configuration of physical products. Our aim was to study what major ideas from KBC can be applied to SVM, particularly in the context of CSPLs. Our main contribution is the identification of major ideas from KBC that could be applied to SVM. First, we call for the separation of types and instances. Second, conceptual clarity of modelling concepts, e.g., having both taxonomical and compositional relations would be useful. Third, we argue for the importance of a conceptual basis that provides a foundation for multiple representations, e.g., graphical and textual. Applying the insights and experiences embedded in these ideas may help in the development of modelling support for software product lines, particularly in terms of conceptual clarity and as a basis for tool support with a high level of automation.Peer reviewe

Personalization for unobtrusive service interaction

Increasingly, mobile devices play a key role in the communication between users and the services embedded in their environment. With ever greater number of services added to our surroundings, there is a need to personalize services according to the user needs and environmental context avoiding service behavior from becoming overwhelming. In order to prevent this information overload, we present a method for the development of mobile services that can be personalized in terms of obtrusiveness (the degree in which each service intrudes the user's mind) according to the user needs and preferences. That is, services can be developed to provide their functionality at different obtrusiveness levels depending on the user by minimizing the duplication of efforts. On the one hand, we provide mechanisms for describing the obtrusiveness degree required for a service. On the other hand, we make use of Feature Modeling techniques in order to define the obtrusiveness level adaptation in a declarative manner. An experiment was conducted in order to put in practice the proposal and evaluate the user acceptance for the personalization capabilities provided by our approach. © Springer-Verlag London Limited 2011.This work has been developed with the support of MICINN under the project EVERYWARE TIN2010-18011 and co-financed with ERDF, in the grants program FPU.Gil Pascual, M.; Giner Blasco, P.; Pelechano Ferragud, V. (2012). Personalization for unobtrusive service interaction. Personal and Ubiquitous Computing. 16(5):543-561. https://doi.org/10.1007/s00779-011-0414-0S543561165Abrams M, Phanouriou C, Batongbacal AL, Williams SM, Shuster JE (1999) Uiml: an appliance-independent xml user interface language. In: WWW ’99. Elsevier, North-Holland, pp 1695–1708Ballagas R, Borchers J, Rohs M, Sheridan JG (2006) The smart phone: a ubiquitous input device. IEEE Pervas Comput 5(1):70Balme L, Demeure A, Barralon N, Coutaz J, Calvary G (2004) Cameleon-rt: a software architecture reference model for distributed, migratable, and plastic user interfaces. In: EUSAI, pp 291–302Benavides D, Cortés RA, Trinidad P (2005) Automated reasoning on feature models. In: LNCS, advanced information systems engineering: 17th international conference, CAiSE 2005 3520, pp 491–503Blomquist A, Arvola M (2002) Personas in action: ethnography in an interaction design team. In: Proceedings of NordiCHI ’02. ACM, New York, NY, pp 197–200Bright A, Kay J, Ler D, Ngo K, Niu W, Nuguid A (2005) Adaptively recommending museum tours. In: Nick Ryan Tullio Salmon Cinotti GR (ed) Proceedings of workshop on smart environments and their applications to cultural heritage. Archaeolingua, pp 29–32Brown DM (2010) Communicating design: developing web site documentation for design and planning, 2nd edn. New Riders Press, USACalvary G, Coutaz J, Thevenin D, Limbourg Q, Bouillon L, Vanderdonckt J (2003) A unifying reference framework for multi-target user interfaces. Interact Comput 15(3):289–308Cetina C, Giner P, Fons J, Pelechano V (2009) Autonomic computing through reuse of variability models at runtime: the case of smart homes. Computer 42(10):37–43Chatfield C, Carmichael D, Hexel R, Kay J, Kummerfeld B (2005) Personalisation in intelligent environments: managing the information flow. In: OZCHI ’05. Computer-human interaction special interest group of Australia, pp 1–10Clerckx T, Winters F, Coninx K (2005) Tool support for designing context-sensitive user interfaces using a model-based approach. In: TAMODIA ’05: Proceedings of the 4th international workshop on Task models and diagrams. ACM Press, New York, pp 11–18Czarnecki K, Helsen S, Eisenecker U (2004) Staged configuration using feature models. In: Proceedings of SPLCDuarte C, Carriço L (2006) A conceptual framework for developing adaptive multimodal applications. In: Proceedings of IUI ’06. ACM, New York, pp 132–139Evans (2003) Domain-driven design: tacking complexity In the heart of software. Addison-Wesley Longman Publishing Co., Inc., BostonsFavre JM (2004) Foundations of model (Driven) (Reverse) engineering: models—Episode I: stories of the fidus papyrus and of the solarus. In: Bezivin J, Heckel R (eds) Language engineering for model-driven software development, no. 04101, Dagstuhl seminar proceedings. Dagstuhl, GermanyFischer G (2001) User modeling in human–computer interaction. User Model User-Adap Inter 11(1–2):65–86Gibbs WW (2005) Considerate computing. Scientific American 292(1):54–61Giner P, Cetina C, Fons J, Pelechano V (2010) Developing mobile workflow support in the internet of things. IEEE Pervas Comput 9(2):18–26Giner P, Cetina C, Fons J, Pelechano V (2011) Implicit interaction design for pervasive workflows. Pers Ubiquit Comput 1–10Gulliksen J, Goransson B, Boivie I, Blomkvist S, Persson J, Cajander A (2003) Key principles for user-centred systems design. Behav Inform Technol 22:397–409Hinckley K, Horvitz E (2001) Toward more sensitive mobile phones. In: Proceedings of the UIST ’01. ACM, New York, pp 191–192Ho J, Intille SS (2005) Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. In: Proceedings of CHI ’05. ACM, New York, pp 909–918Horvitz E, Kadie C, Paek T, Hovel D (2003) Models of attention in computing and communication: from principles to applications. Commun ACM 46(3):52–59Ju W, Leifer L (2008) The design of implicit interactions: making interactive systems less obnoxious. Des Issues 24(3):72–84Lewis JR (1995) Ibm computer usability satisfaction questionnaires: psychometric evaluation and instructions for use. Int J Hum-Comput Interact 7(1):57–78Limbourg Q, Vanderdonckt J, Michotte B, Bouillon L, López-Jaquero V (2004) Usixml: a language supporting multi-path development of user interfaces. In: EHCI/DS-VIS, pp 200–220Mao JY, Vredenburg K, Smith PW, Carey T (2001) User-centered design methods in practice: a survey of the state of the art. In: CASCON ’01. IBM Press, New York, p 12McCrickard DS, Chewar CM (2003) Attuning notification design to user goals and attention costs. Commun ACM 46:67–72Mori G, Paternò F, Santoro C (2002) Ctte: support for developing and analyzing task models for interactive system design. IEEE Trans Softw Eng 28(8):797–813Mori G, Paternò F, Santoro C (2004) Design and development of multidevice user interfaces through multiple logical descriptions. IEEE Trans Softw Eng 30(8):507–520Myers B, Hudson SE, Pausch R (2000) Past, present, and future of user interface software tools. ACM Trans Comput-Hum Interact 7(1):3–28OMG (2006) Business process modeling notation (BPMN) specification. OMG Final Adopted SpecificationPaternò F, Santoro C (2003) A unified method for designing interactive systems adaptable to mobile and stationary platforms. Interact Comput 15(3):349–366Puerta A, Eisenstein J (2002) Ximl: a common representation for interaction data. In: Proceedings of IUI ’02. ACM, New York, pp 214–215Ramchurn SD, Deitch B, Thompson MK, Roure DCD, Jennings NR, Luck M (2004) Minimising intrusiveness in pervasive computing environments using multi-agent negotiation. In: First international conference on mobile and ubiquitous systems, pp 364–372Rumbaugh J, Jacobson I, Booch G (1998) The unified modeling language reference manual. Addison-Wesley, LondonSchobbens PY, Heymans P, Trigaux JC, Bontemps Y (2007) Generic semantics of feature diagrams. Comput Networks 51(2):456–479Serral E, Pérez F, Valderas P, Pelechano V (2010) An end-user tool for adapting smart environment automation to user behaviour at runtime. In: Proceedings of UCAmI ’10Streefkerk JW, van Esch-Bussemakers MP, Neerincx MA (2006) Designing personal attentive user interfaces in the mobile public safety domain. Comput Hum Behav 22:749–770Tedre M (2008) What should be automated? Interactions 15(5):47–49Unger R, Chandler C (2009) A project guide to UX design: for user experience designers in the field or in the making. New Riders Publishing, Thousand OaksVan den Bergh J, Coninx K. Using uml 2.0 and profiles for modelling context-sensitive user interfaces. In: Proceedings of the MDDAUI2005 CEUR workshopVastenburg MH, Keyson DV, de Ridder H (2008) Considerate home notification systems: a field study of acceptability of notifications in the home. Pers Ubiquit Comput 12(8):555–566Vertegaal R (2003) Attentive user interfaces. Commun ACM 46(3):30–33Weiser M, Brown JS (1997) The coming age of calm technology, pp 75–85Weld DS, Anderson C, Domingos P, Etzioni O, Gajos K, Lau T, Wolf S (2003) Automatically personalizing user interfaces. In: IJCAI ’03, pp 1613–161

Automated Analysis in Feature Modelling and Product Configuration

The automated analysis of feature models is one of the thriving topics of research in the software product line and variability management communities that has attracted more attention in the last years. A recent literature review reported that more than 30 analysis operations have been identi ed and di erent analysis mechanisms have been proposed. Product con guration is a well established research eld with more than 30 years of successful applications in di erent industrial domains. Our hypothesis, that is not really new, is that these two independent areas of research have interesting synergies that have not been fully explored. To try to explore the potential synergies systematically, in this paper we provide a rapid review to bring together these previously disparate streams of work. We de ne a set of research questions and give a preliminary answer to some of them. We conclude that there are many research opportunities in the synergy of these independent areas.Ministerio de Ciencia e Innovación TIN2009- 07366Junta de Andalucía TIC-590

Logics of knowledge and action: critical analysis and challenges

International audienceWe overview the most prominent logics of knowledge and action that were proposed and studied in the multiagent systems literature. We classify them according to these two dimensions, knowledge and action, and moreover introduce a distinction between individual knowledge and group knowledge, and between a nonstrategic an a strategic interpretation of action operators. For each of the logics in our classification we highlight problematic properties. They indicate weaknesses in the design of these logics and call into question their suitability to represent knowledge and reason about it. This leads to a list of research challenges