Uncertainty-Wise Cyber-Physical System test modeling

Lee, E.A.: Cyber physical systems: design challenges. In: 2008 11th IEEE International Symposium on Object Oriented Real-Time Distributed Computing (ISORC), pp. 363–369 (2008)

Rawat, D.B., Rodrigues, J.J., Stojmenovic, I.: Cyber-Physical Systems: From Theory to Practice. CRC Press, Boca Raton (2015)

Sunder, S.: Foundations for innovation in Cyber-Physical Systems. In: Proceedings of the NIST CPS Workshop, Chicago, IL, USA

Geisberger, E., Broy, M.: Living in a Networked World: Integrated Research Agenda Cyber-Physical Systems (agendaCPS). Herbert Utz Verlag, Munich (2015)

Bammer, G., Smithson, M.: Uncertainty and Risk: Multidisciplinary Perspectives. Routledge, Abingdon (2012)

Lindley, D.V.: Understanding Uncertainty (Revised Edition). Wiley, Hoboken (2014)

Zhang, M., Selic, B., Ali, S., Yue, T., Okariz, O., Norgren, R.: Understanding uncertainty in Cyber-Physical Systems: a conceptual model. In: Proceedings of the 12th European Conference on Modelling Foundations and Applications (ECMFA), pp. 247–264

Ali, S., Yue, T.: U-test: evolving, modelling and testing realistic uncertain behaviours of Cyber-Physical Systems. In: Proceedings of the IEEE 8th International Conference on Software Testing, Verification and Validation (ICST), pp. 1–2

Future Position X. http://www.fpx.se/ . Accessed 2017

ULMA Handling System. http://www.ulmahandling.com/en/ . Accessed 2017

Object Management Group (OMG): UML profile for MARTE: modeling and analysis of real-time embedded systems, Version 1.1. http://www.omg.org/spec/MARTE/ (2011)

IBM Rational Software Architect Modeling Tool. https://www.ibm.com/developerworks/downloads/r/architect/ . Accessed 2016

CertifyIt. http://www.smartesting.com/en/certifyit/ . Accessed 2017

Easy Global Market. http://www.eglobalmark.com/ . Accessed 2017

Nordic Med Test. http://www.nordicmedtest.se/ . Accessed 2017

IK4-IKERLAN. http://www.ikerlan.es/eu/ . Accessed 2017

Cisco. http://www.cisco.com/ . Accessed 2017

Ali, S., Briand, L.C., Hemmati, H.: Modeling robustness behavior using aspect-oriented modeling to support robustness testing of industrial systems. Softw. Syst. Model. 11(4), 633–670 (2012)

Pressman, R.S.: Software Engineering: A Practitioner’s Approach, 7th edn. Palgrave Macmillan, Basingstoke (2010)

Object Management Group (OMG): UML testing profile, Version 1.2. http://www.omg.org/spec/UTP/ (2013)

Ali, S., Yue, T., Hoffmann, A., Wendland, M.F., Bagnato, A., Brosse, E., Schacher, M., Dai, Z.R.: How does the UML testing profile support risk-based testing. In: 2014 IEEE International Symposium on Software Reliability Engineering Workshops, pp. 311–316

UML Testing Profile $$^{{\rm TM}}$$ TM (UTP) 2.0. http://utp.zen-tools.com/

Object Management Group (OMG): UML testing profile, Version 2. http://utp.omg.org/ , http://www.omg.org/cgi-bin/doc?ad/16-05-10 (2016)

IBM: UML Action Language (UAL). https://www.ibm.com/support/knowledgecenter/SS8PJ7_9.6.0/com.ibm.xtools.model.ual.doc/topics/c_umlactionlanguage.html (2017). Accessed 2017

Zhang, M., Ali, S., Yue, T., Nguyen, P.H.: Uncertainty Modeling Framework for the Integration Level V.1. Technical Report 2016-01 Simula Research Laboratory, 2016. https://www.simula.no/publications/uncertainty-modeling-framework-integration-level-v1 (2016)

Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)

Dempster, A.P.: Upper and lower probabilities induced by a multivalued mapping. Ann. Math. Stat. 38(2), 325–339 (1967)

Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)

Hartley, R.V.L.: Transmission of information. Bell Syst. Tech. J. 7(3), 535–563 (1928)

Lamata, M.T., Moral, S.: Measures of entropy in the theory of evidence. Int. J. Gen. Syst. 14(4), 297–305 (1988)

Yager, R.R.: Entropy and specificity in a mathematical theory of evidence. Int. J. Gen. Syst. 9(4), 249–260 (1983)

Higashi, M., Klir, G.J.: Measures of uncertainty and information based on possibility distributions. Int. J. Gen. Syst. 9(1), 43–58 (1982)

Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 1(1), 3–28 (1978)

Smets, P., Kennes, R.: The transferable belief model. Artif. Intell. 66(2), 191–234 (1994)

George, J.K., Bo, Y.: Fuzzy sets and fuzzy logic, theory and applications (2008)

Kosko, B.: Fuzzy entropy and conditioning. Inf. Sci. 40(2), 165–174 (1986)

Didier, D., Henri, P.: Fuzzy Sets and Systems: Theory and Application. Mathematics in Science and Engineering, vol. 144. Academic Press, Cambridge (1980)

Zimmermann, H.-J.: Fuzzy Set Theory—And Its Applications. Springer, Berlin (2011)

Pawlak, Z.: Rough sets. Int. J. Comput. Inf. Sci. 11(5), 341–356 (1982)

Goguen, J.A.: L-fuzzy sets. J. Math. Anal. Appl. 18(1), 145–174 (1967)

Atanassov, K., Georgiev, C.: Intuitionistic fuzzy prolog. Fuzzy Sets Syst. 53(2), 121–128 (1993)

Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning—I. Inf. Sci. 8(3), 199–249 (1975)

Grattan-Guinness, I.: Fuzzy membership mapped onto intervals and many-valued quantities. Math. Logic Q. 22(1), 149–160 (1976)

Jahn, K.U.: Intervall-wertige Mengen. Math. Nachr. 68(1), 115–132 (1975)

Gau, W.L., Buehrer, D.J.: Vague sets. IEEE Trans. Syst. Man Cybern. 23(2), 610–614 (1993)

De Luca, A., Termini, S.: A definition of a nonprobabilistic entropy in the setting of fuzzy sets theory. Inf. Control 20(4), 301–312 (1972)

Feller, W.: An Introduction to Probability Theory and Its Applications. Wiley, Hoboken (2008)

Song, H., Rawat, D.B., Jeschke, S., Brecher, C.: Cyber-Physical Systems: Foundations, Principles and Applications. Morgan Kaufmann, Burlington (2016)

Talcott, C.: Cyber-Physical Systems and events. In: Wirsing, M., Banâtre, J.-P., Hölzl, M., Rauschmayer, A. (eds.) Software-Intensive Systems and New Computing Paradigms: Challenges and Visions, pp. 101–115. Springer, Berlin (2008)

Ali, S., Briand, L.C., Rehman, M.J.-U., Asghar, H., Iqbal, M.Z.Z., Nadeem, A.: A state-based approach to integration testing based on UML models. Inf. Softw. Technol. 49(11–12), 1087–1106 (2007)

Eclipse OCL. http://www.eclipse.org/modeling/mdt/?project=ocl-ocl . Accessed 2016

Dresden OCL. https://marketplace.eclipse.org/content/dresden-ocl . Accessed April, 2016

IBM RSA Simulation Toolkit. http://www-03.ibm.com/software/products/en/ratisoftarchsimutool . Accessed 2016

Use Cases—Industrial Case Studies. http://www.u-test.eu/use-cases/ . Accessed 2017

Certus. http://certus-sfi.no/ . Accessed 2017

Schneider, M., Wendland, M.-F.: Gaining certainty about uncertainty: testing for uncertainties of Cyber-Physical Systems at the application level. In: 4th International Workshop on Risk Assessment and Risk-driven Quality Assurance (RISK), In Conjunction with 28th International Conference on Testing Software and Systems (ICTSS) (2016)

Kerwin, A.: None too solid medical ignorance. Sci. Commun. 15(2), 166–185 (1993)

Object Management Group (OMG):Concrete syntax For A UML action language: action language for foundational UML (ALF), Version 1.0.1. http://www.omg.org/spec/ALF/ (2013)

Sicilia, M.-A., Mastorakis, N.: Extending UML 1. 5 for fuzzy conceptual modeling: an strictly additive approach. WSEAS Trans. Syst. 3(5), 2234–2239 (2004)

Ma, Z.: Fuzzy information modeling with the UML. Advances in fuzzy object oriented databases: modeling and applications. Idea Group Inc., USA, 153–75 (2004)

Ma, Z.M., Zhang, F., Yan, L.: Fuzzy information modeling in UML class diagram and relational database models. Appl. Soft Comput. 11(6), 4236–4245 (2011)

Yan, L., Ma, Z.M. : Extending nested relational model for fuzzy information modeling. In: 2009 WASE International Conference on Information Engineering, pp. 587–590 (2009)

Ma, Z.M., Zhang, F., Yan, L., Cheng, J.: Representing and reasoning on fuzzy UML models: a description logic approach. Expert Syst. Appl. 38(3), 2536–2549 (2011)

Zhang, F., Ma, Z.M.: Construction of fuzzy ontologies from fuzzy UML models. Int. J. Comput. Intell. Syst. 6(3), 442–472 (2013)

Haroonabadi, A., Teshnehlab, M., Movaghar, A.: A novel method for behavior modeling in uncertain information systems. World Acad. Sci. Eng. Technol. 41, 959–966 (2008)

Motameni, H., Daneshfar, I., Bakhshi, J., Nematzadeh, H.: Transforming fuzzy state diagram to fuzzy Petri net. J. Adv. Comput. Res. 1(1), 29–44 (2010)

Grassi, V., Mirandola, R.: UML modelling and performance analysis of mobile software architectures. In: UML 2001—The Unified Modeling Language. Modeling Languages, Concepts, and Tools, pp. 209–224. Springer (2001)

Garousi, V.: Traffic-aware stress testing of distributed real-time systems based on UML models in the presence of time uncertainty. In: 2008 1st International Conference on Software Testing, Verification, and Validation, pp. 92–101

Object Management Group (OMG): UML profile for schedulability, performance, and time, Version 1.1. http://www.omg.org/spec/SPTP/ (2005)

Riebisch, M., Philippow, I., Götze, M.: UML-based statistical test case generation. In: Aksit, M., Mezini, M., Unland, R. (eds.) Objects, Components, Architectures, Services, and Applications for a Networked World. NODe 2002. Lecture Notes in Computer Science, vol. 2591, pp. 394–411. Springer, Berlin (2002)

Salay, R., Famelis, M., Chechik, M.: Language independent refinement using partial modeling. In: de Lara, J., Zisman, A. (eds.) Fundamental Approaches to Software Engineering. FASE 2012. Lecture Notes in Computer Science, vol. 7212, pp. 224–239. Springer, Berlin (2012)

Famelis, M., Salay, R., Chechik, M.: Partial models: towards modeling and reasoning with uncertainty. In: 2012 34th International Conference on Software Engineering (ICSE), pp. 573–583 (2012)

Famelis, M., Santosa, S.: MAV-Vis: a notation for model uncertainty. In: 2013 5th International Workshop on Modeling in Software Engineering (MiSE), pp. 7–12 (2013)

Garvey, P.R., Lansdowne, Z.F.: Risk matrix: an approach for identifying, assessing, and ranking program risks. Air Force J. Logist. 22(1), 18–21 (1998)

Klir, G.: Facets of Systems Science. Springer, Berlin (2013)