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Model execution tracing: a systematic mapping study

  • Fazilat Hojaji
  • Tanja Mayerhofer
  • Bahman ZamaniEmail author
  • Abdelwahab Hamou-Lhadj
  • Erwan Bousse
Regular Paper

Abstract

Model-Driven Engineering is a development paradigm that uses models instead of code as primary development artifacts. In this paper, we focus on executable models, which are used to abstract the behavior of systems for the purpose of verifying and validating (V&V) a system’s properties. Model execution tracing (i.e., obtaining and analyzing traces of model executions) is an important enabler for many V&V techniques including testing, model checking, and system comprehension. This may explain the increase in the number of proposed approaches on tracing model executions in the last years. Despite the increased attention, there is currently no clear understanding of the state of the art in this research field, making it difficult to identify research gaps and opportunities. The goal of this paper is to survey and classify existing work on model execution tracing, and identify promising future research directions. To achieve this, we conducted a systematic mapping study where we examined 64 primary studies out of 645 found publications. We found that the majority of model execution tracing approaches has been developed for the purpose of testing and dynamic analysis. Furthermore, most approaches target specific modeling languages and rely on custom trace representation formats, hindering the synergy among tools and exchange of data. This study also revealed that most existing approaches were not validated empirically, raising doubts as to their effectiveness in practice. Our results suggest that future research should focus on developing a common trace exchange format for traces, designing scalable trace representations, as well as conducting empirical studies to assess the effectiveness of proposed approaches.

Keywords

Model-driven engineering Executable models Model execution tracing Dynamic analysis of model-driven systems Systematic mapping study 

Notes

Acknowledgements

This work is partially supported by Iranian Ministry of Science, Research and Technology and Isfahan University under the IMPULS Iran–Austria Contract No. 4/11937.

References

  1. 1.
    Adams, R.J., Smart, P., Huff, A.S.: Shades of grey: guidelines for working with the grey literature in systematic reviews for management and organizational studies. Int. J. Manag. Rev. 19(4), 432–454 (2017)Google Scholar
  2. 2.
    Alawneh, L., Hamou-Lhadj, A.: Execution Traces: A New Domain that Requires the Creation of a Standard Metamodel, Volume 59 of Lecture Notes in Communications in Computer and Information Science Book Series, pp. 253–263. Springer, Berlin (2009)Google Scholar
  3. 3.
    Alawneh, L., Hamou-Lhadj, A.: An exchange format for representing dynamic information generated from high performance computing applications. Future Gener. Comput. Syst. 27(4), 381–394 (2011)Google Scholar
  4. 4.
    Aljamaan, H., Lethbridge, T.C.: Towards tracing at the model level. In: Proceedings of the 19th Working Conference on Reverse Engineering (WCRE), pp. 495–498. IEEE (2012)Google Scholar
  5. 5.
    Aljamaan, H., Lethbridge, T.C., Badreddin, O., Guest, G., Forward, A.: Specifying trace directives for UML attributes and state machines. In: Proceedings of the 2nd International Conference on Model-Driven Engineering and Software Development (MODELSWARD), pp. 79–86. IEEE (2014)Google Scholar
  6. 6.
    Aljamaan, H., Lethbridge, T.C., Garzón, M.A.: MOTL: a textual language for trace specification of state machines and associations. In: Proceedings of the 25th Annual International Conference on Computer Science and Software Engineering, CASCON ’15, pp. 101–110. IBM Corp., Riverton (2015)Google Scholar
  7. 7.
    Aljamaan, H.I., Lethbridge, T., Garzón, M., Forward, A.: UmpleRun: a dynamic analysis tool for textually modeled state machines using Umple. In: Proceedings of the First International Workshop on Executable Modeling Co-located with MODELS 2015, pp. 16–20 (2015)Google Scholar
  8. 8.
    Barr, E.T., Marron, M.: Tardis: affordable time-travel debugging in managed runtimes. In: Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages and Applications (OOPSLA’14), pp. 67–82. ACM (2014)Google Scholar
  9. 9.
    Bousse, E., Combemale, B., Baudry, B.: Towards scalable multidimensional execution traces for xDSMLs. In: Proceedings of the 11th Workshop on Model Design, Verification and Validation Integrating Verification and Validation in MDE (MoDeVVa 2014), vol. 1235, pp. 13–18 (2014)Google Scholar
  10. 10.
    Bousse, E., Corley, J., Combemale, B., Gray, J., Baudry, B.: Supporting efficient and advanced omniscient debugging for xDSMLs. In: Proceedings of the ACM SIGPLAN International Conference on Software Language Engineering, pp. 137–148. ACM (2015)Google Scholar
  11. 11.
    Bousse, E., Degueule, T., Vojtisek, D., Mayerhofer, T., DeAntoni, J., Combemale, B.: Execution framework of the GEMOC studio (tool demo). In: Proceedings of the 2016 ACM SIGPLAN International Conference on Software Language Engineering (SLE’16), pp. 84–89. ACM (2016)Google Scholar
  12. 12.
    Bousse, E., Leroy, D., Combemale, B., Wimmer, M., Baudry, B.: Omniscient debugging for executable DSLs. J. Syst. Softw. 137, 261–288 (2018)Google Scholar
  13. 13.
    Bousse, E., Mayerhofer, T., Combemale, B., Baudry, B.: A generative approach to define rich domain-specific trace metamodels. In: European Conference on Modelling Foundations and Applications, Volume 9153 of Lecture Notes in Computer Science, pp. 45–61. Springer, Berlin (2015)Google Scholar
  14. 14.
    Bousse, E., Mayerhofer, T., Combemale, B., Baudry, B.: Advanced and efficient execution trace management for executable domain-specific modeling languages. Softw. Syst. Model. 1, 1–37 (2017)Google Scholar
  15. 15.
    Brambilla, M., Jordi, C., Wimmer, M.: Model-Driven Software Engineering in Practice. Synthesis Lectures on Software Engineering, 2nd edn. Morgan & Claypool Publishers, San Rafael (2017)Google Scholar
  16. 16.
    Brereton, P., Kitchenham, B.A., Budgen, D., Turner, M., Khalil, M.: Lessons from applying the systematic literature review process within the software engineering domain. J. Syst. Softw. 80(4), 571–583 (2007)Google Scholar
  17. 17.
    Bryant, B.R., Gray, J., Mernik, M., Clarke, P.J., France, R.B., Karsai, G.: Challenges and directions in formalizing the semantics of modeling languages. Comput. Sci. Inf. Syst. 2(8), 225–253 (2011)Google Scholar
  18. 18.
    Calvez, J.P.: Embedded Real-Time Systems. A Specification and Design Methodology. Wiley, New York (1993)Google Scholar
  19. 19.
    Ciccozzi, F., Malavolta, I., Selic, B.: Execution of UML models: a systematic review of research and practice. Softw. Syst. Model. 1, 1–48 (2018)Google Scholar
  20. 20.
    Combemale, B., Crégut, X., Garoche, P.-L., Thirioux, X.: Essay on semantics definition in MDE. An instrumented approach for model verification. J. Softw. (JSW) 4(9), 943–958 (2009)Google Scholar
  21. 21.
    Combemale, B., Crégut, X., Pantel, M.: A design pattern to build executable DSMLs and associated V&V tools. In: Proceedings of the 19th Asia–Pacific on Software Engineering Conference (APSEC), vol. 1, pp. 282–287. IEEE (2012)Google Scholar
  22. 22.
    Combemale, B., Crgut, X., Giacometti, J.-P., Michel, P., Pantel, M.: Introducing simulation and model animation in the MDE Topcased toolkit. In: Proceedings of the 4th European Congress Embedded Real Time Software (ERTS) (2008)Google Scholar
  23. 23.
    Combemale, B., Gonnord, L., Rusu, R.: A generic tool for tracing executions back to a DSMLs operational semantics. In: European Conference on Modelling Foundations and Applications, vol. 6698, pp. 35–51 (2011)Google Scholar
  24. 24.
    Cornelissen, B., Zaidman, A., Van Deursen, A., Moonen, L., Koschke, R.: A systematic survey of program comprehension through dynamic analysis. IEEE Trans. Softw. Eng. 35(5), 684–702 (2009)Google Scholar
  25. 25.
    Cornelissen, B., Zaidman, A., van Deursen, A., Moonen, L., Koschke, R.: A systematic survey of program comprehension through dynamic analysis. IEEE Trans. Softw. Eng. 35, 684–702 (2009)Google Scholar
  26. 26.
    Crane, M.L., Dingel, J.: Towards a UML virtual machine: implementing an interpreter for UML 2 actions and activities. In: Conference of the Center for Advanced Studies on Collaborative Research, pp. 96–110. ACM (2008)Google Scholar
  27. 27.
    Cuadros López, Á.J., Galindres, C., Ruiz, P.: Project maturity evaluation model for SMEs from the software development sub-sector. AD-Minister 29, 147–162 (2016)Google Scholar
  28. 28.
    Damm, W., Harel, D.: LSCs: breathing life into message sequence charts. Form. Methods Syst. Des. 19(1), 45–80 (2001)zbMATHGoogle Scholar
  29. 29.
    De Antoni, J., Mallet, F.: Timesquare: treat your models with logical time. In: Proceedings of the International Conference on Objects, Models, Components, Patterns (TOOLS), vol. 7304, pp. 34–41. Springer, Berlin (2012)Google Scholar
  30. 30.
    De Antoni, J., Mallet, F., Thomas, F., Reydet, G., Babau, J.-P., Mraidha, C., Gauthier, L., Rioux, L., Sordon, N.: RT-simex: retro-analysis of execution traces. In: Proceedings of the 18th ACM SIGSOFT International Symposium on Foundations of Software Engineering, pp. 377–378. ACM (2010)Google Scholar
  31. 31.
    Derezinska, A., Szczykulski, M.: Tracing of state machine execution in the model-driven development framework. In: Proceedings of the 2nd International Conference on Information Technology, ICIT 2010, pp. 517–524. IEEE (2010)Google Scholar
  32. 32.
    Deshayes, R., Meyers, B., Mens, T., Vangheluwe, H.: ProMoBox in practice: a case study on the GISMO Domain-specific modelling language. In: Proceedings of the 8th Workshop on Multi-Paradigm Modelling (MPM), pp. 21–30 (2014)Google Scholar
  33. 33.
    Dias Neto, A.C., Subramanyan, R., Vieira, M., Travassos, G.H.: A survey on model-based testing approaches: a systematic review. In: Proceedings of the 1st ACM International Workshop on Empirical Assessment of Software Engineering Languages and Technologies: Held in Conjunction with the 22nd IEEE/ACM International Conference on Automated Software Engineering (ASE) 2007, pp. 31–36. ACM (2007)Google Scholar
  34. 34.
    do Nascimento, L.M., Viana, D.L., Neto, P.A.M.S., Martins, D.A.O., Garcia, V.C., Meira, S.R.L.: A systematic mapping study on domain specific languages. In: Proceedings of the 7th International Conference on Software Engineering Advances (ICSEA12), pp. 179–187 (2012)Google Scholar
  35. 35.
    Domínguez, E., Pérez, B., Zapata, M.A.: A UML profile for dynamic execution persistence with monitoring purposes. In: Proceedings of the 5th International Workshop on Modeling in Software Engineering, pp. 55–61. IEEE (2013)Google Scholar
  36. 36.
    Faria, J.P., Paiva, A.C.R.: A toolset for conformance testing against UML sequence diagrams based on event-driven colored petri nets. Int. J. Softw. Tools Technol. Transf. 18(3), 285–304 (2016)Google Scholar
  37. 37.
    Fernández-Fernández, C.A., Simons, A.J.H.: An implementation of the task algebra, a formal specification for the task model in the discovery method. J. Appl. Res. Technol. 12(5), 908–918 (2014)Google Scholar
  38. 38.
    Fernández-Fernández, C.A., Simons, A.J.H.: An algebra to represent task flow models. Int. J. Comput. Intell. Theory Pract. 6(2), 63–74 (2011)Google Scholar
  39. 39.
    Fischer, T., Niere, J., Torunski, L., Zündorf, A.: Story diagrams: a new graph rewrite language based on the unified modeling language and java. In: Proceedings of the 6th International Workshop on the Theory and Application of Graph Transformations (TAGT’98), Volume 1764 of Lecture Notes in Computer Science, pp. 296–309. Springer, Berlin (1998)Google Scholar
  40. 40.
    Fuentes, L., Manrique, J., Sánchez, P.: Execution and simulation of (profiled) UML models using Populo. In: Proceedings of the International Workshop on Models in Software Engineering, pp. 75–81. ACM (2008)Google Scholar
  41. 41.
    Fuentes, L., Sánchez, P.: Designing and weaving aspect-oriented executable UML models. J. Object Technol. 6(7), 109–136 (2007)Google Scholar
  42. 42.
    Fuentes, L., Sánchez, P.: Towards executable aspect-oriented UML models. In: Proceedings of the 10th International Workshop on Aspect-Oriented Modeling, pp. 28–34. ACM (2007)Google Scholar
  43. 43.
    Fuentes, L., Sánchez, P.: Dynamic weaving of aspect-oriented executable UML models. Trans. Asp. Oriented Softw. Dev. 5560, 1–38 (2009)Google Scholar
  44. 44.
    Garcés, K., Deantoni, J., Mallet, F.: A model-based approach for reconciliation of polychromous execution traces. In: Proceedings of the 37th EUROMICRO Conference on Software Engineering and Advanced Applications (SEAA), pp. 259–266. IEEE (2011)Google Scholar
  45. 45.
    Giraldo, F.D., Espana, S., Pastor, O.: Analyzing the concept of quality in model-driven engineering literature: a systematic review. In: Proceedings of the 8th International Conference on Research Challenges in Information Science (RCIS), pp. 1–12. IEEE (2014)Google Scholar
  46. 46.
    Goel, A., Sengupta, B., Roychoudhury, A.: Footprinter: round-trip engineering via scenario and state based models. In: Proceedings of the 31st International Conference on Software Engineering—Companion Volume, ICSE-Companion, pp. 419–420. IEEE (2009)Google Scholar
  47. 47.
    Gogolla, M., Hamann, L., Hilken, F., Kuhlmann, M., France, R.B.: From application models to filmstrip models: an approach to automatic validation of model dynamics. In: Modellierung, vol. 225, pp. 273–288 (2014)Google Scholar
  48. 48.
    Gurbuz, H.G., Tekinerdogan, B.: Model-based testing for software safety: a systematic mapping study. Softw. Qual. J. 26, 1–46 (2017)Google Scholar
  49. 49.
    Haberl, W., Birke, J., Baumgarten, U.: A middleware for model-based embedded systems. In: Proceedings of the International Conference on Embedded Systems and Applications (ESA), pp. 253–259 (2008)Google Scholar
  50. 50.
    Haberl, W., Herrmannsdoerfer, M., Birke, J., Baumgarten, U.: Model-level debugging of embedded real-time systems. In: Proceedings of the 10th International Conference on Computer and Information Technology (CIT), pp. 1887–1894. IEEE (2010)Google Scholar
  51. 51.
    Hamou-Lhadj, A.: Techniques to simplify the analysis of execution traces for program comprehension. Doctoral Dissertation, University of Ottawa Ottawa, Ontario (2006)Google Scholar
  52. 52.
    Hamou-Lhadj, A., Lethbridge, T.: A metamodel for dynamic information generated from object-oriented systems. Electron. Notes Theor. Comput. Sci. 94, 59–69 (2004)Google Scholar
  53. 53.
    Hamou-Lhadj, A., Lethbridge, T.: A survey of trace exploration tools and techniques. In: Proceedings of the 2004 Conference of the Centre for Advanced Studies on Collaborative Research, CASCON ’04, pp. 42–55. IBM Press (2004)Google Scholar
  54. 54.
    Hamou-Lhadj, A., Lethbridge, T.: Summarizing the content of large traces to facilitate the understanding of the behaviour of a software system. In: Proceedings of the 14th International Conference on Program Comprehension, ICPC, pp. 181–190. IEEE (2006)Google Scholar
  55. 55.
    Hamou-Lhadj, A., Lethbridge, T.: A metamodel for the compact but lossless exchange of execution traces. Softw. Syst. Model. 11(1), 7798 (2012)Google Scholar
  56. 56.
    Hegedus, A., Bergmann, G., Ráth, I., Varró, D.: Back-annotation of simulation traces with change-driven model transformations. In: Proceedings of the 8th IEEE International Conference on Software Engineering and Formal Methods (SEFM), pp. 145–155. IEEE (2010)Google Scholar
  57. 57.
    Hegedus, A., Bergmann, G., Ráth, I., Varró, D.: Replaying execution trace models for dynamic modeling languages. Period. Polytechn. Electr. Eng. Comput. Sci. 56(3), 71–82 (2013)Google Scholar
  58. 58.
    Hendriks, M., Vaandrager, F.W.: Reconstructing critical paths from execution traces. In: Proceedings of the 15th International Conference on Computational Science and Engineering (CSE), pp. 524–531. IEEE (2012)Google Scholar
  59. 59.
    Hendriks, M., Verriet, J., Basten, T., Theelen, B., Brassé, M., Somers, L.: Analyzing execution traces: critical-path analysis and distance analysis. Int. J. Softw. Tools Technol. Transf. 19(4), 487–512 (2016)Google Scholar
  60. 60.
    Hilken, F., Gogolla, M.: Verifying linear temporal logic properties in UML/OCL class diagrams using filmstripping. In: Proceedings of the Euromicro Conference on Digital System Design (DSD), pp. 708–713. IEEE (2016)Google Scholar
  61. 61.
    Hilken, F., Hamann, L., Gogolla, M.: Transformation of UML and OCL models into filmstrip models. In: International Conference on Theory and Practice of Model Transformations, Volume 8568 of Lecture Notes in Computer Science, pp. 170–185. Springer, Berlin (2014)Google Scholar
  62. 62.
    Hojaji, F., Zamani, B., Hamou-Lhadj, A.: Towards a tracing framework for model-driven software systems. In: Proceedings of the 6th International Conference on Computer and Knowledge Engineering (ICCKE), pp. 298–303. IEEE (2016)Google Scholar
  63. 63.
    Hu, Z., Shatz, S.M.: Mapping UML diagrams to a petri net notation for system simulation. In: Proceedings of the International Conference on Software Engineering and Knowledge Engineering (SEKE), pp. 213–219. Citeseer (2004)Google Scholar
  64. 64.
    Intana, A., Poppleton, M.R., Merrett, G.V.: A model-based trace testing approach for validation of formal co-simulation models. In: Proceedings of the Symposium on Theory of Modeling and Simulation: DEVS Integrative M&S Symposium, pp. 181–188. Society for Computer Simulation International (2015)Google Scholar
  65. 65.
    Jhala, R., Majumdar, R.: Software model checking. ACM Comput. Surv. 41(4), 21:1–21:54 (2009)Google Scholar
  66. 66.
    Kelly, S., Tolvanen, J.-P.: Domain-Specific Modeling: Enabling Full Code Generation. Wiley, New York (2008)Google Scholar
  67. 67.
    Kemper, P., Tepper, C.: Automated analysis of simulation traces-separating progress from repetitive behavior. In: Proceedings of the Fourth International Conference on the Quantitative Evaluation of Systems. QEST 2007, pp. 101–110. IEEE (2007)Google Scholar
  68. 68.
    Kemper, P., Tepper, C.: Automated trace analysis of discrete-event system models. IEEE Trans. Softw. Eng. 35(2), 195–208 (2009)Google Scholar
  69. 69.
    Kitchenham, B., Charters, S.: Guidelines for Performing Systematic Literature Reviews in Software Engineering. Report, Software Engineering Group, School of Computer Science and Mathematics, Keele University (2000)Google Scholar
  70. 70.
    Kraft, J., Wall, A., Kienle, H.M.: Trace recording for embedded systems: lessons learned from five industrial projects. In: Proceedings of the International Conference on Runtime Verification, Volume 6418 of Lecture Notes in Computer Science, pp. 315–329. Springer, Berlin (2010)Google Scholar
  71. 71.
    Krasnogolowy, A., Hildebrandt, S., Wätzoldt, S.: Flexible debugging of behavior models. In: IEEE International Conference on Industrial Technology (ICIT), pp. 331–336. IEEE (2012)Google Scholar
  72. 72.
    Kugele, S., Tautschnig, M., Bauer, A., Schallhart, C., Merenda, S., Haberl, W., Kühnel, C., Müller, F., Wang, Z., Wild, D., et al.: COLA—The Component Language. Technical Report (2007)Google Scholar
  73. 73.
    Langer, P., Mayerhofer, T., Kappel, G.: Semantic model differencing utilizing behavioral semantics specifications. In: Proceedings of the International Conference on Model Driven Engineering Languages and Systems, Volume 8767 of Lecture Notes in Computer Science, pp. 116–132. Springer, Berlin (2014)Google Scholar
  74. 74.
    Li, L., Li, X., Tang, S.: Research on web application consistency testing based on model simulation. In: Proceedings of the 9th International Conference on Computer Science and Education (ICCSE), pp. 1121–1127. IEEE (2014)Google Scholar
  75. 75.
    Lian, J., Hu, Z., Shatz, S.M.: Simulation-based analysis of UML statechart diagrams: methods and case studies. Softw. Qual. J. 16(1), 45–78 (2008)Google Scholar
  76. 76.
    Lima, B., Faria, J.P.: An approach for automated scenario-based testing of distributed and heterogeneous systems. In: Proceedings of the 10th International Joint Conference on Software Technologies (ICSOFT), vol. 1, pp. 1–10. IEEE (2015)Google Scholar
  77. 77.
    Maoz, S.: Model-based traces. In: Proceedings of the International Conference on Model Driven Engineering Languages and Systems, Volume 5421 of Lecture Notes in Computer Science, pp. 109–119. Springer, Berlin (2009)Google Scholar
  78. 78.
    Maoz, S.: Using model-based traces as runtime models. IEEE Comput. Soc. 42, 28–36 (2009)Google Scholar
  79. 79.
    Maoz, S., Harel, D.: On tracing reactive systems. Softw. Syst. Model. 10(4), 447–468 (2011)Google Scholar
  80. 80.
    Maoz, S., Ringert, J.O., Rumpe, B.: ADDiff: semantic differencing for activity diagrams. In: Proceedings of the 19th ACM SIGSOFT Symposium and the 13th European Conference on Foundations of Software Engineering, pp. 179–189. ACM (2011)Google Scholar
  81. 81.
    Maoz, S., Ringert, J.O., Rumpe, B.: Summarizing Semantic Model Differences. arXiv preprint arXiv:1409.2307 (2014)
  82. 82.
    Mayerhofer, T.: Testing and debugging UML models based on fUML. In: Proceedings of the 34th International Conference on Software Engineering (ICSE), pp. 1579–1582. IEEE (2012)Google Scholar
  83. 83.
    Mayerhofer, T., Langer, P., Kappel, G.: A runtime model for fUML. In: Proceedings of the 7th Workshop on Models@ run time, pp. 53–58. ACM (2012)Google Scholar
  84. 84.
    Mayerhofer, T., Langer, P., Wimmer, M., Kappel, G.: xMOF: executable DSMLs based on fUML. In: Proceedings of the International Conference on Software Language Engineering, Volume 8225 of Lecture Notes in Computer Science, pp. 56–75. Springer, Berlin (2013)Google Scholar
  85. 85.
    Mehner, K.: JaVis: a UML-based visualization and debugging environment for concurrent Java programs. Softw. Vis. 2269, 163–175 (2002)zbMATHGoogle Scholar
  86. 86.
    Meyers, B., Deshayes, R., Lucio, L., Syriani, E., Vangheluwe, H., Wimmer, M.: ProMoBox: a framework for generating domain-specific property languages. In: Proceedings of the International Conference on Software Language Engineering (SLE), Volume 8706 of Lecture Notes in Computer Science, pp. 1–20. Springer, Berlin (2014)Google Scholar
  87. 87.
    Mijatov, S., Langer, P., Mayerhofer, T., Kappel, G.: A framework for testing UML activities based on fUML. In: Proceedings of the 10th International Workshop on Model Driven Engineering, Verification and Validation Co-located with 16th International Conference on Model Driven Engineering Languages and Systems (MODELS 2013), vol. 1069, pp. 1–10. Springer, Berlin (2013)Google Scholar
  88. 88.
    Mijatov, S., Mayerhofer, T., Langer, P., Kappel, G.: Testing functional requirements in UML activity diagrams. In: International Conference on Tests and Proofs, Volume 9154 of Lecture Notes in Computer Science, pp. 173–190. Springer, Berlin (2015)Google Scholar
  89. 89.
    Nguyen, P.H., Kramer, M., Klein, J., Traon, Y.L.: An extensive systematic review on the model-driven development of secure systems. Inf. Softw. Technol. 68, 62–81 (2015)Google Scholar
  90. 90.
    Object Management Group: Business Process Model and Notation (BPMN), Version 2.0 (2011)Google Scholar
  91. 91.
    Object Management Group: Semantics of a Foundational Subset for Executable UML Models (fUML), Version 1.3 (2017)Google Scholar
  92. 92.
    Pasquier, O., Calvez, J.P.: An object-based executable model for simulation of real-time Hw/Sw systems. In: Proceedings of the Design, Automation and Test in Europe Conference and Exhibition, pp. 782–783. IEEE (1999)Google Scholar
  93. 93.
    Petersen, K., Vakkalanka, S., Kuzniarz, L.: Guidelines for conducting systematic mapping studies in software engineering: an update. Inf. Softw. Technol. 64, 1–18 (2015)Google Scholar
  94. 94.
    Petri, C.A.: Fundamentals of a Theory of Asynchronous Information Flow. In: Proceedings of IFIP Congress, pp. 386–390. North Holland, Amsterdam (1962)Google Scholar
  95. 95.
    Rumbaugh, J., Blaha, M., Premerlani, W., Eddy, F., Lorensen, W.E., et al.: Object-Oriented Modeling and Design, vol. 199. Prentice-Hall, Englewood Cliffs (1991)zbMATHGoogle Scholar
  96. 96.
    Santiago, I., Jimnez, A., Vara, J.M., De Castro, V., Bollati, V.A., Marcos, E.: Model-driven engineering as a new landscape for traceability management: a systematic literature review. Inf. Softw. Technol. 54(12), 1340–1356 (2012)Google Scholar
  97. 97.
    Schivo, S., Yildiz, B.M., Ruijters, E., Gerking, C., Kumar, R., Dziwok, S., Rensink, A., Stoelinga, M.: How to efficiently build a front-end tool for UPPAAL: a model-driven approach. In: International Symposium on Dependable Software Engineering: Theories, Tools, and Applications, Volume 10606 of Lecture Notes in Computer Science, pp. 319–336. Springer, Berlin (2017)Google Scholar
  98. 98.
    Schmidt, D.C.: Guest editor’s introduction: model-driven engineering. IEEE Comput. 39(2), 25–31 (2006)MathSciNetGoogle Scholar
  99. 99.
    Scopus. A Generic Framework for Realizing Semantic Model Differencing Operators, vol. 1258 (2014)Google Scholar
  100. 100.
    Scott, D.: Outline of a Mathematical Theory of Computation. Oxford University Computing Laboratory, Programming Research Group, Oxford (1970)Google Scholar
  101. 101.
    Szvetits, M., Zdun, U.: Systematic literature review of the objectives, techniques, kinds, and architectures of models at runtime. Softw. Syst. Model. 15(1), 31–69 (2013)Google Scholar
  102. 102.
    Tatibouet, J., Cuccuru, A., Gérard, S., Terrier, F.: Formalizing execution semantics of UML profiles with fUML models. In: Proceedings of the 17th International Conference on Model-Driven Engineering Languages and Systems (MODELS’14), Volume 8767 of Lecture Notes in Computer Science, pp. 133–148. Springer, Berlin (2014)Google Scholar
  103. 103.
    Wang, L., Wong, E., Xu, D.: A threat model driven approach for security testing. In: Proceedings of the 3th International Workshop on Software Engineering for Secure Systems, ICSE Workshops, pp. 10–17. IEEE (2007)Google Scholar
  104. 104.
    Wehrmeister, M.A., Packer, J.G., Ceron, L.M.: Framework to simulate the behavior of embedded real-time systems specified in UML models. In: Brazilian Symposium on Computing System Engineering (SBESC), pp. 1–7. IEEE (2011)Google Scholar
  105. 105.
    Wehrmeister, M.A., Packer, J.G., Ceron, L.M., Pereira, C.E.: Towards early verification of UML models for embedded and real-time systems. Embed. Syst. Comput. Intell. Telemat Control 45(4), 25–30 (2012)Google Scholar
  106. 106.
    Yilmaz, L.: Automated object-flow testing of dynamic process interaction models. In: Proceedings of the Simulation Conference, Proceedings of the Winter, vol. 1, pp. 586–594. IEEE (2001)Google Scholar

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Authors and Affiliations

  1. 1.MDSE Research Group, Department of Software EngineeringUniversity of IsfahanIsfahanIran
  2. 2.Business Informatics GroupTU WienViennaAustria
  3. 3.Intelligent System-Logging and Monitoring Research Lab, Department of Electrical and Computer EngineeringConcordia UniversityMontréalCanada

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