A. E. Haxthausen and J. Peleska, Formal development and verification of a distributed railway control system, Software Engineering IEEE Transactions, vol.26, pp.687-701, 2000.

Y. Choe, S. Lee, and M. Lee, SAVE: An Environment for Visual Specification and Verification of IoT, Enterprise Distributed Object Computing Workshop, pp.1-8, 2016.
DOI : 10.1109/edocw.2016.7584384

M. Lee, Composition Model for Cloud Services with Behavior Ontology, COMPSACW, 2013.

R. Mcnaughton and H. Yamada, Regular expressions and state graphs for automata, IRE transactions on Electronic Computers, vol.9, issue.1, pp.39-47, 1960.

Y. Choe and M. Lee, A Lattice Model to Verify Behavioral Equivalence, 2014 UKSim-AMSS 8th European Modelling Symposium, 2014.

H. G. Fill and D. Karagiannis, On the conceptualisation of modelling methods using the ADOxx meta modelling platform, Enterprise Modeling and Information Systems Architectures, vol.8, pp.4-25, 2013.

Y. Choe and M. Lee, A Process Algebra Construct Method for Reduction of States in Reachability Graph: Conjunctive and Complement Choices, In: Journal of KIISE, vol.43, issue.5, pp.541-552, 2016.

A. Yassine, S. Singh, A. , and A. , Mining human activity patterns from smart home big data for health care applications, IEEE Access, vol.5, pp.13131-13141, 2017.
DOI : 10.1109/access.2017.2719921

E. M. Clarke, E. Emerson, and J. Sifakis, Model Checking: Algorithmic Verification and Debugging, Communications of the ACM, vol.52, issue.11, pp.74-84, 2009.

W. J. Yeh and M. Young, Compositional Reachability Analysis Using Process Algebra, Proceedings of the symposium on Testing, analysis, and verification, pp.49-59, 1992.
DOI : 10.1145/120807.120812

T. Chen, A Compositional Specification Theory for Component Behaviors, European Symposium on Programming, pp.148-168, 2012.
DOI : 10.1007/978-3-642-28869-2_8

URL : http://hal.inria.fr/docs/00/66/55/99/PDF/esop12.pdf

S. C. Raju, An Automatic Verification Technique for Communicating Real-Time State Mechines, 1993.

M. Rahmani, J. Song, and M. Lee, PRISM: A Knowledge Engineering Tool to Model Collective Behaviors of Real-time IoT Systems, Practicing Open Enterprise Modeling, 2017.