Abstract
Cyber-physical systems (CPSs) have emerged as a potential enabling technology to handle the challenges in social and economic sustainable development. Since it was proposed in 2006, intensive research has been conducted, showing that the construction of a CPS is a hard and complex engineering process due to the nature of integrating a large number of heterogeneous subsystems. Among other approaches to dealing with the complex design issues, model-driven design of CPSs has shown its advantages. In this review paper, we present a survey of research on model-driven development of CPSs. We are concerned mainly with the widely used methods, techniques, and tools, and discuss how these are applied to CPSs. We also present comparative analyses on the surveyed techniques and tools from various perspectives, including their modeling languages, functionalities, and the challenges which they address in CPS design. With our understanding of the surveyed methods, we believe that model-driven approaches are an inevitable choice in building CPSs and further research effort is needed in the development of model-driven theories, techniques, and tools. We also argue that a unified modeling platform is needed. Such a platform would benefit research in the academic community and practical development in industry, and improve the collaboration between these two communities.
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References
Abrial JR, 2005. The B-Book: Assigning Programs to Meanings. Cambridge University Press, Cambridge, UK.
Abrial JR, Butler M, Hallerstede S, et al., 2010. Rodin: an open toolset for modelling and reasoning in Event-B. Int J Softw Tools Technol Transfer, 12(6):447–466. https://doi.org/10.1007/s10009-010-0145-y
Amrani M, Lucio L, Selim G, et al., 2012. A tridimensional approach for studying the formal verification of model transformations. Proc IEEE 5th Int Conf on Software Testing, Verification and Validation, p.921–928. https://doi.org/10.1109/ICST.2012.197
Banach R, Butler M, Qin SC, et al., 2015. Core Hybrid Event-B I: single Hybrid Event-B machines. Sci Comput Program, 105:92–123. https://doi.org/10.1016/j.scico.2015.02.003
Banach R, Butler M, Qin SC, et al., 2017. Core Hybrid Event-B II: multiple cooperating Hybrid Event-B machines. Sci Comput Program, 139:1–35. https://doi.org/10.1016/j.scico.2016.12.003
Banerjee A, Kandula S, Mukherjee T, et al., 2012. BAND-AiDe: a tool for cyber-physical oriented analysis and design of body area networks and devices. ACM Trans Embed Comput Syst, 11(S2):49. https://doi.org/10.1145/2331147.2331159
Bernardeschi C, Domenici A, Masci P, 2018. A PVS-Simulink integrated environment for model-based analysis of cyber-physical systems. IEEE Trans Softw Eng, 44(6):512–533. https://doi.org/10.1109/TSE.2017.2694423
Bocciarelli P, D’Ambrogio A, Giglio A, et al., 2017. A BPMN extension for modeling cyber-physical-production-systems in the context of Industry 4.0. IEEE 14th Int Conf on Networking, Sensing and Control, p.599–604. https://doi.org/10.1109/ICNSC.2017.8000159
Booch G, Rumbaugh J, Jacobson I, 1999. The Unified Modeling Language User Guide. Addison Wesley Longman Publishing Co., Inc., USA.
Boronat A, Carsí JA, Ramos I, 2006. Exogenous model merging by means of model management operators. Proc 3rd Workshop on Software Evolution Through Transformations: Embracing the Change, p.1–19. https://doi.org/10.14279/tuj.eceasst.3.8
Brau G, Navet N, Hugues J, 2017. Heterogeneous models and analyses in the design of real-time embedded systems—an avionic case-study. Proc 25th Int Conf on Real-Time Networks and Systems, p.168–177. https://doi.org/10.1145/3139258.3139281
Braun W, Casella F, Bachmann B, 2017. Solving large-scale Modelica models: new approaches and experimental results using OpenModelica. Proc 12th Int Modelica Conf, p.557–563. https://doi.org/10.3384/ecp17132557
Broman D, Lee EA, Tripakis S, et al., 2012. Viewpoints, formalisms, languages, and tools for cyber-physical systems. Proc 6th Int Workshop on Multi-paradigm Modeling, p.49–54. https://doi.org/10.1145/2508443.2508452
Brown AW, 2004. Model driven architecture: principles and practice. Softw Syst Model, 3(4):314–327. https://doi.org/10.1007/s10270-004-0061-2
Broy M, Cengarle MV, Geisberger E, 2012. Cyber-physical systems: imminent challenges. In: Calinescu R, Garlan D (Eds.), Large-Scale Complex IT Systems. Development, Operation and Management. Springer, Berlin, p. 1–28. https://doi.org/10.1007/978-3-642-34059-8_1
Cabot J, Gogolla M, 2012. Object Constraint Language (OCL): a definitive guide. Proc 12th Int Conf on Formal Methods for the Design of Computer, Communication, and Software Systems: Formal Methods for Model-Driven Engineering, p.58–90. https://doi.org/10.1007/978-3-642-30982-3_3
Calegari D, Szasz N, 2013. Verification of model transformations: a survey of the state-of-the-art. Electron Notes Theor Comput Sci, 292:5–25. https://doi.org/10.1016/j.entcs.2013.02.002
Chen LP, Babar MA, Nuseibeh B, 2013. Characterizing architecturally significant requirements. IEEE Softw, 30(2):38–45. https://doi.org/10.1109/MS.2012.174
Chen X, Liu ZM, 2017. Towards interface-driven design of evolving component-based architectures. In: Hinchey M, Bowen JP, Olderog ER (Eds.), Provably Correct Systems. Springer, Cham, p.121–148. https://doi.org/10.1007/978-3-319-48628-4_6
Cicchetti A, di Ruscio D, Eramo R, et al., 2010. JTL: a bidirectional and change propagating transformation language. Proc 3rd Int Conf on Software Language Engineering, p.183–202. https://doi.org/10.1007/978-3-642-19440-5_11
Clarke EM, 2008. The birth of model checking. In: Grumberg O, Veith H (Eds.), 25 Years of Model Checking: History, Achievements, Perspectives. Springer, Berlin, p.1–26. https://doi.org/10.1007/978-3-540-69850-0_1
Czarnecki K, Helsen S, 2003. Classification of model transformation approaches. Proc 2nd OOPSLA Workshop on Generative Techniques in the Context of the Model Driven Architecture, p.1–17.
Derler P, Lee EA, Vincentelli AS, 2012. Modeling cyberphysical systems. Proc IEEE, 100(1):13–28. https://doi.org/10.1109/JPROC.2011.2160929
Eidson JC, Lee EA, Matic S, et al., 2012. Distributed realtime software for cyber-physical systems. Proc IEEE, 100(1):45–59. https://doi.org/10.1109/JPROC.2011.2161237
ESTEREL, 2015. Efficient development of safe avionics software with DO-178C objectives using SCADE Suite®. ESTEREL Technologies. http://www.peraglobal.com/upload/contents/2015/11/20151113142739_85462.pdf [Accessed on Aug. 30, 2020].
Feiler PH, Gluch DP, Hudak JJ, 2006. The Architecture Analysis & Design Language (AADL): an introduction. Software Engineering Institute, p.145. https://doi.org/10.1184/R1/6584909
Fowler M, 2003. UML Distilled: a Brief Guide to the Standard Object Modeling Language (3rd Ed.). Addison-Wesley, Boston, USA.
Friedenthal S, Moore A, Steiner R, 2015. A Practical Guide to SysML: the Systems Modeling Language. Elsevier, Waltham, USA.
Fritzson P, 2014. Principles of Object Oriented Modeling and Simulation with Modelica 3.3: a Cyber-Physical Approach. John Wiley & Sons, Inc. https://doi.org/10.1002/9781118989166
Fulton N, Mitsch S, Quesel JD, et al., 2015. KeYmaera X: an axiomatic tactical theorem prover for hybrid systems. Proc 25th Int Conf on Automated Deduction, p.527–538. https://doi.org/10.1007/978-3-319-21401-6_36
Gill H, 2008. From Vision to Reality: Cyber-Physical Systems. http://labs.ece.uw.edu/nsl/aar-cps/Gill_HCSS_Transportation_Cyber-Physical_Systems_2008.pdf [Accessed on Aug. 30, 2020].
Gunes V, Peter S, Givargis T, et al., 2014. A survey on concepts, applications, and challenges in cyber-physical systems. KSII Trans Int Inform Syst, 8(12):4242–4268. https://doi.org/10.3837/tiis.2014.12.001
Halbwachs N, Caspi P, Raymond P, et al., 1991. The synchronous data flow programming language LUSTRE. Proc IEEE, 79(9):1305–1320. https://doi.org/10.1109/5.97300
He JF, Li Q, 2017. A hybrid relational modelling language. In: Gibson-Robinson T, Hopcroft P, Lazic R (Eds.), Concurrency, Security, and Puzzles: Essays Dedicated to Andrew William Roscoe on the Occasion of His 60th Birthday. Springer, Cham, p.124–143. https://doi.org/10.1007/978-3-319-51046-0_7
Hehenberger P, Vogel-Heuser B, Bradley D, et al., 2016. Design, modelling, simulation and integration of cyber physical systems: methods and applications. Comput Ind, 82:273–289. https://doi.org/10.1016/j.compind.2016.05.006
Henriksson D, Elmqvist H, 2011. Cyber-physical systems modeling and simulation with Modelica. Proc 8th Int Modelica Conf, p.502–509. https://doi.org/10.3384/ecp11063502
Henzinger TA, 1996. The theory of hybrid automata. Proc 11th Annual IEEE Symp on Logic in Computer Science, p.278–292. https://doi.org/10.1109/LICS.1996.561342
Huang P, Jiang KQ, Guan CL, et al., 2018. Towards modeling cyber-physical systems with SysML/MARTE/pCCSL. IEEE 42nd Annual Computer Software and Applications Conf, p.264–269. https://doi.org/10.1109/COMPSAC.2018.00042
Jézéquel JM, Barais O, Fleurey F, 2009. Model driven language engineering with Kermeta. Proc 3rd Int Summer School Conf on Generative and Transformational Techniques in Software Engineering III, p.201–221. https://doi.org/10.1007/978-3-642-18023-1_5
Jirkovský V, Obitko M, Mařík V, 2017. Understanding data heterogeneity in the context of cyber-physical systems integration. IEEE Trans Ind Inform, 13(2):660–667. https://doi.org/10.1109/TII.2016.2596101
Jouault F, Bézivin J, 2006. KM3: a DSL for metamodel specification. Proc 8th IFIP WG 6.1 Int Conf on Formal Methods for Open Object-Based Distributed Systems, p.171–185. https://doi.org/10.1007/11768869_14
Jouault F, Allilaire F, Bézivin J, et al., 2008. ATL: a model transformation tool. Sci Comput Program, 72(1–2):31–39. https://doi.org/10.1016/j.scico.2007.08.002
Juric MB, Mathew B, Sarang P, 2004. Business Process Execution Language for Web Services: BPEL and BPEL4WS. Packt Publishing.
Kleppe A, Warmer J, Bast W, 2003. MDA Explained: the Model Driven Architecture: Practice and Promise. Addison-Wesley, Boston.
Kühne T, 2006. Matters of (meta-) modeling. Softw Syst Model, 5(4):369–385.
Larson BR, Chalin P, Hatcliff J, 2013. BLESS: formal specification and verification of behaviors for embedded systems with software. Proc 5th Int Sympon NASA Formal Methods, p.276–290. https://doi.org/10.1007/978-3-642-38088-4_19
Lasnier G, Cardoso J, Siron P, et al., 2013. Distributed simulation of heterogeneous and real-time systems. Proc IEEE/ACM 17th Int Symp on Distributed Simulation and Real Time Applications, p.55–62. https://doi.org/10.1109/DS-RT.2013.14
Lawley M, Steel J, 2005. Practical declarative model transformation with Tefkat. MoDELS Int Workshops Doctoral Symp, p.139–150. https://doi.org/10.1007/11663430_15
Lee EA, 2008. Cyber physical systems: design challenges. Int Symp on Object/Component/Service-Oriented Real-Time Distributed Computing. http://chess.eecs.berkeley.edu/pubs/427.html
Lee EA, 2010. CPS foundations. Proc 47th Design Automation Conf, p.737–742. http://chess.eecs.berkeley.edu/pubs/804.html
Lee EA, 2018. Modeling in engineering and science. Commun ACM, 62(1):35–36. https://doi.org/10.1145/3231590
Lee EA, Zheng HY, 2005. Operational semantics of hybrid systems. Proc 8th Int Workshop on Hybrid Systems: Computation and Control, p.25–53. https://doi.org/10.1007/978-3-540-31954-2_2
Lee EA, Niknami M, Nouidui TS, et al., 2015. Modeling and simulating cyber-physical systems using CyPhySim. Proc 20th Int Conf on Embedded Software, p.115–124.
Lee J, Bagheri B, Kao HA, 2015. A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manuf Lett, 3:18–23. https://doi.org/10.1016/j.mfglet.2014.12.001
Leino KRM, 2007. Verification of Object-Oriented Software. The KeY Approach. Springer, Berlin.
Liu J, Lv JD, Quan Z, et al., 2010. A calculus for hybrid CSP. Proc 8th Asian Symp on Programming Languages and Systems, p.1–15. https://doi.org/10.1007/978-3-642-17164-2_1
Liu J, Li TF, Ding ZH, et al., 2019. AADL+: a simulation-based methodology for cyber-physical systems. Front Comput Sci, 13(3):516–538. https://doi.org/10.1007/s11704-018-7039-7
Liu Y, Peng Y, Wang BL, et al., 2017. Review on cyber-physical systems. IEEE/CAA J Autom Sin, 4(1):27–40. https://doi.org/10.1109/JAS.2017.7510349
Liu ZM, Chen X, 2016. Model-driven design of object and component systems. Engineering Trustworthy Software Systems, Cham, p.152–255.
Liu ZM, Bowen JP, Liu B, et al., 2019. Software abstractions and human-cyber-physical systems architecture modelling. 5th Int School on Engineering Trustworthy Software Systems, p.159–219. https://doi.org/10.1007/978-3-030-55089-9_5
Lunel S, Mitsch S, Boyer B, et al., 2019. Parallel composition and modular verification of computer controlled systems in differential dynamic logic. In: Ter Beek M, McIver A, Oliveira J (Eds.), Formal Methods—The Next 30 Years. Springer, Cham, p.354–370. https://doi.org/10.1007/978-3-030-30942-8_22
Lynch N, Segala R, Vaandrager F, 2003. Hybrid I/O automata. Inform Comput, 185(1):105–157. https://doi.org/10.1016/S0890-5401(03)00067-1
Maler O, Manna Z, Pnueli A, 1992. From timed to hybrid systems. In: de Bakker JW, Huizing C, de Roever WP, et al. (Eds.), Real-Time: Theory in Practice. Springer, Berlin, p.447–484. https://doi.org/10.1007/BFb0032003
Mallet F, 2015. MARTE/CCSL for modeling cyber-physical systems. In: Drechsler R, Kühne U (Eds.), Formal Modeling and Verification of Cyber-Physical Systems. Springer Vieweg, Wiesbaden, p.26–49. https://doi.org/10.1007/978-3-658-09994-7_2
Mallet F, Villar E, Herrera F, 2017. MARTE for CPS and CPSoS: present and future, methodology and tools. In: Nakajima S, Talpin JP, Toyoshima M, et al. (Eds.), Cyber-Physical System Design from an Architecture Analysis Viewpoint. Springer, Singapore, p.81–108. https://doi.org/10.1007/978-981-10-4436-6_4
Mellor SJ, 2004. MDA Distilled: Principles of Model-Driven Architecture. Addison-Wesley, Boston. http://cds.cern.ch/record/1505924 [Accessed on Aug. 30, 2020].
Mens T, van Gorp P, 2006. A taxonomy of model transformation. Electron Notes Theor Comput Sci, 152:125–142. https://doi.org/10.1016/j.entcs.2005.10.021
Miller J, Mukerji J, 2003. MDA Guide Version 1.0.1. Object Management Group.
Mohamed MA, Challenger M, Kardas G, 2020. Applications of model-driven engineering in cyber-physical systems: a systematic mapping study. J Comput Lang, 59:100972. https://doi.org/10.1016/j.cola.2020.100972
Müller A, Mitsch S, Retschitzegger W, et al., 2016. A component-based approach to hybrid systems safety verification. In: Abraham E, Huisman M (Eds.), Integrated Formal Methods. Springer, Cham, p.441–456. https://doi.org/10.1007/978-3-319-33693-0_28
Nazari S, Sonntag C, Engell S, 2015. A Modelica-based modeling and simulation framework for large-scale cyber-physical systems of systems. IFAC-PapersOnLine, 48(1):920–921. https://doi.org/10.1016/j.ifacol.2015.05.190
Oldevik J, Neple T, Grønmo R, et al., 2005. Toward standardised model to text transformations. Proc 1st European Conf on Model Driven Architecture: Foundations and Applications, p.239–253. https://doi.org/10.1007/11581741_18
Platzer A, 2008. Differential dynamic logic for hybrid systems. J Autora Reason, 41(2):143–189. https://doi.org/10.1007/s10817-008-9103-8
Platzer A, 2010. Logical Analysis of Hybrid Systems: Proving Theorems for Complex Dynamics. Springer, Berlin.
Platzer A, 2018. Logical Foundations of Cyber-Physical Systems. Springer, Cham.
Ptolemaeus C, 2014. System Design, Modeling, and Simulation Using Ptolemy II. http://ptolemy.org/books/Systems [Accessed on Aug. 30, 2020].
Qin ZJ, Do N, Denker G, et al., 2014. Software-defined cyber-physical multinetworks. Int Conf on Computing, Networking and Communications, p.322–326. https://doi.org/10.1109/ICCNC.2014.6785354
Rahim LA, Whittle J, 2015. A survey of approaches for verifying model transformations. Softw Syst Model, 14(2):1003–1028. https://doi.org/10.1007/s10270-013-0358-0
Rajkumar R, Lee I, Sha L, et al., 2010. Cyber-physical systems: the next computing revolution. Design Automation Conf, p.731–736. https://doi.org/10.1145/1837274.1837461
Saeedloei N, Gupta G, 2016. A methodology for modeling and verification of cyber-physical systems based on logic programming. ACM SIGBED Rev, 13(2):34–42. https://doi.org/10.1145/2930957.2930963
Sangiovanni-Vincentelli A, Damm W, Passerone R, 2012. Taming Dr. Frankenstein: contract-based design for cyber-physical systems. Eur J Contr, 18(3):217–238. https://doi.org/10.3166/ejc.18.217-238
Seidewitz E, 2003. What models mean. IEEE Softw, 20(5):26–32. https://doi.org/10.1109/MS.2003.1231147
Selic B, 2003. The pragmatics of model-driven development. IEEE Softw, 20(5):19–25. https://doi.org/10.1109/MS.2003.1231146
Selic B, Gérard S, 2014. Modeling and Analysis of Real-Time and Embedded Systems with UML and MARTE. Elsevier, Amsterdam. https://doi.org/10.1016/C2012-0-13536-5
Sha L, Gopalakrishnan S, Liu X, et al., 2008. Cyber-physical systems: a new frontier. Int Conf on Sensor Networks, Ubiquitous, and Trustworthy Computing, p.1–9. https://doi.org/10.1109/SUTC.2008.85
Simko G, Levendovszky T, Maroti M, et al., 2014. Towards a theory for cyber-physical systems modeling. Proc 4th ACM SIGBED Int Workshop on Design, Modeling, and Evaluation of Cyber-Physical Systems, p.56–61. https://doi.org/10.1145/2593458.2593463
Tan Y, Vuran MC, Goddard S, 2009. Spatio-temporal event model for cyber-physical systems. Proc 29th IEEE Int Conf on Distributed Computing Systems Workshops, p.44–50. https://doi.org/10.1109/ICDCSW.2009.82
Tariq MU, Grijalva S, Wolf M, 2015. A service-oriented, cyber-physical reference model for smart grid. In: Khaitan SK, McCalley JD, Liu CC (Eds.), Cyber Physical Systems Approach to Smart Electric Power Grid. Springer, Berlin, p.25–42.
The Object Management Group, 2000. Meta-data Interchange (XMI) Specification. https://www.omg.org/spec/QVT/1.0/PDF [Accessed on Aug. 30, 2020].
The Object Management Group, 2006. Model Driven Architecture. http://www.omg.org/mda/ [Accessed on Aug. 30, 2020].
The Object Management Group, 2008. Meta Object Facility (MOF) 2.0 Query/View/Transformation Specification. https://www.omg.org/spec/QVT/1.0/PDF [Accessed on Aug. 30, 2020].
The Object Management Group, 2013. Business Process Model and Notation (BPMN) Version 2.0.2.
Tratt L, 2005. Model transformations and tool integration. Softw Syst Model, 4(2):112–122. https://doi.org/10.1007/s10270-004-0070-1
Varró D, Balogh A, 2007. The model transformation language of the VIATRA2 framework. Sci Comput Program, 68(3):214–234. https://doi.org/10.1016/j.scico.2007.05.004
Varró D, Pataricza A, 2003. VPM: a visual, precise and multi-level metamodeling framework for describing mathematical domains and UML (The Mathematics of Metamodeling is Metamodeling Mathematics). Softw Syst Model, 2(3):187–210. https://doi.org/10.1007/s10270-003-0028-8
Wang BB, Baras JS, 2013. HybridSim: a modeling and co-simulation toolchain for cyber-physical systems. 17th IEEE/ACM Int Symp on Distributed Simulation and Real Time Applications, p.33–40. https://doi.org/10.1109/DS-RT.2013.12
Wang J, Zhan NJ, Feng XY, et al., 2019. Overview of formal methods. J Softw, 30(1):33–61 (in Chinese). https://doi.org/10.13328/j.cnki.jos.005652
Wang SL, Zhan NJ, Zou L, 2015. An improved HHL prover: an interactive theorem prover for hybrid systems. Proc 17th Int Conf on Formal Engineering Methods on Formal Methods and Software Engineering, p.382–399. https://doi.org/10.1007/978-3-319-25423-4_25
Wang TX, Truptil S, Benaben F, 2017. An automatic model-to-model mapping and transformation methodology to serve model-based systems engineering. Inform Syst E-Bus Manag, 15(2):323–376. https://doi.org/10.1007/s10257-016-0321-z
W3C, 1999. W3C Recommendation. https://www.w3.org/TR/1999/REC-xslt-19991116
Xue B, She ZK, Easwaran A, 2016. Under-approximating backward reachable sets by polytopes. Proc 28th Int Conf on Computer Aided Verification, p.457–476. https://doi.org/10.1007/978-3-319-41528-4_25
Xue B, Mosaad PN, Fränzle M, et al., 2017. Safe over- and under-approximation of reachable sets for delay differential equations. 15th Int Conf on Formal Modeling and Analysis of Timed Systems, p.97–115. https://doi.org/10.1007/978-3-319-65765-3_16
Younes AB, Hlaoui YB, Ayed LJB, 2014. A meta-model transformation from UML activity diagrams to Event-B models. Proc IEEE 38th Int Computer Software and Applications Conf Workshops, p.740–745. https://doi.org/10.1109/COMPSACW.2014.119
Zhan NJ, Wang SL, Zhao HJ, 2016. Formal Verification of Simulink/Stateflow Diagrams: a Deductive Approach. Springer, Cham, p.1–258.
Zhang LC, Feng SG, 2014. Aspect-oriented QoS modeling of cyber-physical systems by the extension of architecture analysis and design language. Proc Int Conf on Computer Engineering and Network, p.1125–1131. https://doi.org/10.1007/978-3-319-01766-2_128
Acknowledgements
We wish to thank Prof. Nai-jun ZHAN for his technical support on this work, and Prof. Zhiming LIU for his great help on paper design and writing. In addition, Dr. Heng-jun ZHAO provided helpful information on HCSP and Event-B, and Dr. Xia ZENG shared her idea for organizing this paper. We also thank the anonymous referees for helping us improve the paper.
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Project supported by the Special Foundation for Basic Science and Frontier Technology Research Program of Chongqing, China (No. cstc2017jcyjAX0295), the Capacity Development Foundation of Southwest University, China (No. SWU116007), and the National Natural Science Foundation of China (Nos. 62032019, 61732019, 61672435, and 61811530327)
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Tie-xin WANG and Bin GU jointly designed the research. Bo LIU, Yuan-rui ZHANG, Xue-lian CAO, and Yu LIU processed the data. Bo LIU, Tie-xin WANG, and Bin GU drafted the manuscript. Yuan-rui ZHANG, Xue-lian CAO, and Yu LIU helped organize the manuscript. Bo LIU, Tie-xin WANG, and Xue-lian CAO revised and finalized the paper.
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Bo LIU, Yuan-rui ZHANG, Xue-lian CAO, Yu LIU, Bin GU, and Tie-xin WANG declare that they have no conflict of interest.
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Liu, B., Zhang, Yr., Cao, Xl. et al. A survey of model-driven techniques and tools for cyber-physical systems. Front Inform Technol Electron Eng 21, 1567–1590 (2020). https://doi.org/10.1631/FITEE.2000311
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DOI: https://doi.org/10.1631/FITEE.2000311