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Modelling guidance in software engineering: a systematic literature review

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Abstract

Despite potential benefits in Software Engineering, adoption of software modelling in industry is low. Technical issues such as tool support have gained significant research before, but individual guidance and training have received little attention. As a first step towards providing the necessary guidance in modelling, we conduct a systematic literature review to explore the current state of the art. We searched academic literature for guidance on model creation and selected 35 papers for full-text screening through three rounds of selection. We find research on model creation guidance to be fragmented, with inconsistent usage of terminology, and a lack of empirical validation or supporting evidence. We outline the different dimensions commonly used to provide guidance on software and system model creation. Additionally, we provide definitions of the three terms modelling method, style, and guideline as current literature lacks a well-defined distinction between them. These definitions can help distinguishing between important concepts and provide precise modelling guidance.

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Notes

  1. https://doi.org/10.5281/zenodo.7685694.

  2. https://doi.org/10.5281/zenodo.7685694.

  3. 66 papers published from 2013–2017 at EMSE and ESEM.

References

  1. Abbott, R.J.: Program design by informal English descriptions. Commun. ACM 26(11), 882–894 (1983). https://doi.org/10.1145/182.358441

    Article  Google Scholar 

  2. Allinson, C., Hayes, J.: The cognitive style index: a measure of intuition analysis for organizational research. J. Manag. Stud. 33, 119–135 (1996). https://doi.org/10.1111/j.1467-6486.1996.tb00801.x

    Article  Google Scholar 

  3. Autili, M., Grunske, L., Lumpe, M., Pelliccione, P., Tang, A.: Aligning qualitative, real-time, and probabilistic property specification patterns using a structured English grammar. IEEE Trans. Softw. Eng. 41(7), 620–638 (2015). https://doi.org/10.1109/TSE.2015.2398877

    Article  Google Scholar 

  4. Bass, L., Clements, P., Kazman, R.: Software Architecture in Practice. Addison-Wesley Professional (2003)

    Google Scholar 

  5. Becker, J., Rosemann, M., Von Uthmann, C.: Guidelines of business process modeling. In: Business Process Management, pp. 30–49. Springer (2000)

  6. Bézivin, J., Muller, P. (eds.): The Unified Modeling Language, UML’98: Beyond the Notation, First International Workshop, Mulhouse, France, June 3-4, 1998, Selected Papers, Lecture Notes in Computer Science, vol. 1618. Springer (1999). https://doi.org/10.1007/b72309

  7. Bordeleau, F.: A Systematic and Traceable Progression from Scenario Models to Communicating Hierarchical State Machines. Ph.D. thesis. Carleton University (2000)

  8. Brown, W.H., Malveau, R.C., McCormick, H.W.S., Mowbray, T.J.: AntiPatterns: Refactoring Software, Architectures, and Projects in Crisis. John Wiley & Sons, Inc. (1998)

  9. Bruegge, B., Dutoit, A.H.: Object-Oriented Software Engineering Using UML, Patterns, and Java, 3rd edn. Prentice Hall Press (2009)

    Google Scholar 

  10. Burgueño, L., Cabot, J., Wimmer, M., Zschaler, S.: Guest editorial to the theme section on ai-enhanced model-driven engineering. Softw. Syst. Model. 21(3), 963–965 (2022)

    Article  Google Scholar 

  11. Cai, L., Chang, C.K., Cleland-Huang, J.: Supporting agent-based distributed software development through modeling and simulation. In: The Ninth IEEE Workshop on Future Trends of Distributed Computing Systems, 2003. FTDCS 2003. Proceedings, pp. 56–62. IEEE (2003)

  12. Cámara, J., Troya, J., Burgueño, L., Vallecillo, A.: On the assessment of generative ai in modeling tasks: an experience report with chatgpt and uml. Softw. Syst. Model. 1–13 (2023)

  13. Chaaben, M.B., Burgueño, L., Sahraoui, H.: Towards using few-shot prompt learning for automating model completion. arXiv preprint arXiv:2212.03404 (2022)

  14. Claes, J., Vanderfeesten, I., Gailly, F., Grefen, P., Poels, G.: The structured process modeling theory (spmt) a cognitive view on why and how modelers benefit from structuring the process of process modeling. Inf. Syst. Front. 17, 1401–1425 (2015). https://doi.org/10.1007/s10796-015-9585-y

    Article  Google Scholar 

  15. Claes, J., Vanderfeesten, I., Pinggera, J., Reijers, H.A., Weber, B., Poels, G.: A visual analysis of the process of process modeling. Inf. Syst. e-Bus. Manag. 13(1), 147–190 (2015)

    Article  Google Scholar 

  16. Corallo, A., Paolis, P., Ippoliti, M., Lazoi, M., Scalvenzi, M., Secundo, G.: Guidelines of a unified approach for product and business process modeling in complex enterprise. Knowl. Process Manag. (2011). https://doi.org/10.1002/kpm.381

    Article  Google Scholar 

  17. Corradini, F., Pettinari, S., Re, B., Rossi, L., Tiezzi, F.: A bpmn-driven framework for multi-robot system development. Robot. Auton. Syst. 160, 104,322 (2023)

    Article  Google Scholar 

  18. Das, T., Dingel, J.: Model development guidelines for uml-rt: conventions, patterns and antipatterns. Softw. Syst. Model. (2018). https://doi.org/10.1007/s10270-016-0549-6

    Article  Google Scholar 

  19. Deng, F., Yan, Y., Gao, F., Wu, L.: Modeling and simulation of cps based on sysml and modelica (kg). In: Proceedings of the 31st International Conference on Software Engineering & Knowledge Engineering SEKE 2019 (2019)

  20. Douglass, B.P.: Doing hard time: developing real-time systems with UML, objects, frameworks, and patterns, vol. 1. Addison-Wesley Professional (1999)

  21. Dwyer, M.B., Avrunin, G.S., Corbett, J.C.: Property specification patterns for finite-state verification. In: Proceedings of the Second Workshop on Formal Methods in Software Practice, pp. 7–15. ACM (1998)

  22. Dwyer, M.B., Avrunin, G.S., Corbett, J.C.: Patterns in property specifications for finite-state verification. In: Proceedings of the 1999 International Conference on Software Engineering (IEEE Cat. No. 99CB37002), pp. 411–420. IEEE (1999)

  23. Fang, J., Zhu, Z., Li, S., Su, H., Yu, Y., Zhou, J., You, Y.: Parallel training of pre-trained models via chunk-based dynamic memory management. IEEE Trans. Parallel Distrib. Syst. 34(1), 304–315 (2022)

    Article  Google Scholar 

  24. Fatwanto, A., Boughton, C.: Architecture modeling for translative model-driven development. In: 2008 International Symposium on Information Technology, vol. 1, pp. 1–9 (2008). https://doi.org/10.1109/ITSIM.2008.4631619

  25. Fernandes, J., Machado, R., Santos, H.: Modeling industrial embedded systems with uml. In: Proceedings of the Eighth International Workshop on Hardware/Software Codesign. CODES 2000, pp. 18–22 (2000). https://doi.org/10.1109/HSC.2000.843700

  26. Firesmith, D.: Use case modeling guidelines. In: Proceedings of Technology of Object-Oriented Languages and Systems - TOOLS 30 (Cat. No.PR00278), pp. 184–193 (1999). https://doi.org/10.1109/TOOLS.1999.787548

  27. Fleiss, J.L., Levin, B., Paik, M.C.: Statistical Methods for Rates and Proportions. Wiley (2013)

    Google Scholar 

  28. Frank, U.: Prolegomena of a multi-level modeling method illustrated with the fmml x. In: 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), pp. 521–530. IEEE (2021)

  29. Gamma, E.: Design patterns: elements of reusable object-oriented software. Pearson Education India (1995)

  30. Giraldo, F.D., España, S., Pastor, O.: Analysing the concept of quality in model-driven engineering literature: a systematic review. In: 2014 IEEE Eighth International Conference on Research Challenges in Information Science (RCIS), pp. 1–12. IEEE (2014)

  31. Gonçalves, M., Fernandes, J.M.: Guidelines for modelling reactive systems with coloured petri nets. In: Machado, R.J., Maciel, R.S.P., Rubin, J., Botterweck, G. (eds.) Model-Based Methodologies for Pervasive and Embedded Software, pp. 126–137. Springer, Berlin Heidelberg, Berlin, Heidelberg (2013)

    Chapter  Google Scholar 

  32. Goncalves, R.F., Menolli, A., Dionisio, G.M.: Mdd4cpd: model driven development approach proposal for cyber-physical devices. In: Anais do XVIII Simpósio Brasileiro de Sistemas de Informação. SBC (2022)

  33. Grunske, L.: Specification patterns for probabilistic quality properties. In: 2008 ACM/IEEE 30th International Conference on Software Engineering, pp. 31–40. IEEE (2008)

  34. Guiochet, J., Motet, G., Baron, C., Boy, G.: Toward a human-centered uml for risk analysis: Application to a medical robot. In: Human Error, Safety and Systems Development: IFIP 18th World Computer Congress TC13/WC13. 5 7th Working Conference on Human Error, Safety and Systems Development 22–27 August 2004 Toulouse, France, pp. 177–191. Springer (2004)

  35. Guizzardi, G., das Graças, A.P., Guizzardi, R.S.S.: Design patterns and inductive modeling rules to support the construction of ontologically well-founded conceptual models in ontouml. In: C. Salinesi, O. Pastor (eds.) Advanced Information Systems Engineering Workshops, pp. 402–413. Springer, Berlin, Heidelberg (2011)

  36. Gwet, K.L.: Handbook of Inter-rater Reliability Advanced Analytics. LLC, Gaithersburg, MD (2010)

    Google Scholar 

  37. Harbo, S.K.R., Kristensen, M.K., Voldby, E.P., Andersen, S.V., Petersen, F.C., Albano, M.: Communication oriented modeling of evolving systems of systems. In: 2021 16th International Conference of System of Systems Engineering (SoSE), pp. 88–94. IEEE (2021)

  38. Hennicker, R., Koch, N.: A uml-based methodology for hypermedia design. In: Evans, A., Kent, S., Selic, B. (eds.) \(\ll \) UML \(\gg \) 2000 – The Unified Modeling Language, pp. 410–424. Springer, Berlin Heidelberg, Berlin, Heidelberg (2000)

    Chapter  Google Scholar 

  39. Hutchinson, J., Rouncefield, M., Whittle, J.: Model-driven engineering practices in industry. In: 33rd International Conference on Software Engineering (ICSE ’11), pp. 633–642 (2011)

  40. Hutchinson, J., Whittle, J., Rouncefield, M.: Model-driven engineering practices in industry: social, organizational and managerial factors that lead to success or failure. Sci. Comput. Program. 89(Part B), 144–161 (2014)

    Article  Google Scholar 

  41. Hutchinson, J., Whittle, J., Rouncefield, M., Kristoffersen, S.: Empirical assessment of MDE in industry. In: 33rd International Conference on Software Engineering (ICSE ’11), pp. 471–480 (2011)

  42. Isaksen, S., Kaufmann, A., Bakken, B.T.: An examination of the personality constructs underlying dimensions of creative problem-solving style. J. Creat. Behavi. 50, 268–281 (2016)

    Article  Google Scholar 

  43. Juhrisch, M., Dietz, G.: Context-based modeling: introducing a novel modeling approach. In: Esswein, W., Turowski, K., Juhrisch, M. (eds.) Modellierung betrieblicher Informationssysteme (MobIS 2010). Modellgestütztes Management, pp. 111–130. Gesellschaft für Informatik e.V., Bonn (2010)

  44. Kaewkasi, C., Rivepiboon, W.: Wwm: a practical methodology for web application modeling. In: Proceedings 26th Annual International Computer Software and Applications, pp. 603–608 (2002). https://doi.org/10.1109/CMPSAC.2002.1045070

  45. Kharchenko, V., Fesenko, H., Illiashenko, O.: Quality models for artificial intelligence systems: characteristic-based approach, development and application. Sensors 22(13), 4865 (2022)

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  46. Kılıç, S.: Kappa testi. J. Mood Disord. 5(3) (2015)

  47. Kitchenham, B., Brereton, P., Budgen, D., Turner, M., Bailey, J., Linkman, S.: Systematic literature reviews in software engineering-a systematic literature review. Inf. Softw. Technol. 51, 7–15 (2009). https://doi.org/10.1016/j.infsof.2008.09.009

    Article  Google Scholar 

  48. Kitchenham, B.A., Charters, S.: Guidelines for performing systematic literature reviews in software engineering. Tech. Rep. EBSE 2007-001, Keele University and Durham University Joint Report (2007)

  49. Kuhrmann, M., Méndez Fernández, D., Daneva, M.: On the pragmatic design of literature studies in software engineering: an experience-based guideline. Empir. Softw. Eng. 22, 2852–2891 (2017). https://doi.org/10.1007/s10664-016-9492-y

    Article  Google Scholar 

  50. Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics 159–174 (1977)

  51. Langford, M.A., Chan, K.H., Fleck, J.E., McKinley, P.K., Cheng, B.H.: Modalas: model-driven assurance for learning-enabled autonomous systems. In: 2021 ACM/IEEE 24th International Conference on Model Driven Engineering Languages and Systems (MODELS), pp. 182–193. IEEE (2021)

  52. Liebel, G.: Model-Based Requirements Engineering in the Automotive Industry: Challenges and Opportunities. Chalmers Tekniska Högskola (Sweden) (2016)

  53. Liebel, G., Marko, N., Tichy, M., Leitner, A., Hansson, J.: Model-based engineering in the embedded systems domain: an industrial survey on the state-of-practice. Softw. Syst. Model. 17(1), 91–113 (2018). https://doi.org/10.1007/s10270-016-0523-3

    Article  Google Scholar 

  54. Liebel, G., Tichy, M., Knauss, E.: Use, potential, and showstoppers of models in automotive requirements engineering. Softw. Syst. Model. (2018). https://doi.org/10.1007/s10270-018-0683-4

    Article  Google Scholar 

  55. Lohmeyer, Q., Meboldt, M., et al.: How we understand engineering drawings: an eye tracking study investigating skimming and scrutinizing sequences. In: International conference on engineering design ICED, vol. 15 (2015)

  56. Long, F., Mohindra, D., Seacord, R.C., Sutherland, D.F., Svoboda, D.: Java Coding Guidelines: 75 Recommendations for Reliable and Secure Programs. Addison-Wesley (2013)

  57. Loniewski, G., Insfran, E., Abrahão, S.: A systematic review of the use of requirements engineering techniques in model-driven development. In: International Conference on Model Driven Engineering Languages and Systems, pp. 213–227. Springer (2010)

  58. Lunkeit, A., Pohl, H.: Model-based security engineering for secure systems development. In: ARCS Workshop 2018; 31th International Conference on Architecture of Computing Systems, pp. 1–10. VDE (2018)

  59. Machado, R.J., Fernandes, J.M., Barros, J.P., Gomes, L.: Scenario-based modeling in industrial information systems. In: Hinchey, M., Kleinjohann, B., Kleinjohann, L., Lindsay, P.A., Rammig, F.J., Timmis, J., Wolf, M. (eds.) Distributed, Parallel and Biologically Inspired Systems, pp. 19–30. Springer, Berlin Heidelberg, Berlin, Heidelberg (2010)

    Chapter  Google Scholar 

  60. Maier, A., Baltsen, N., Christoffersen, H., Störrle, H.: Towards diagram understanding: a pilot study measuring cognitive workload through eye-tracking. In: Proceedings of International Conference on Human Behaviour in Design 2014 (2014)

  61. Maoz, S., Ringert, J.O.: Gr(1) synthesis for ltl specification patterns. In: Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, ESEC/FSE 2015, pp. 96–106. Association for Computing Machinery (2015). https://doi.org/10.1145/2786805.2786824

  62. Marincic, J., Mader, A., Wupper, H., Wupper, H., Wieringa, R.: Non-monotonic modelling from initial requirements: a proposal and comparison with monotonic modelling methods. In: Proceedings of the 3rd International Workshop on Applications and Advances of Problem Frames, pp. 67–73 (2008). https://doi.org/10.1145/1370811.1370825

  63. Mendling, J., Reijers, H., Aalst, W.: Seven process modeling guidelines (7pmg). Inf. Softw. Technol. 52, 127–136 (2010). https://doi.org/10.1016/j.infsof.2009.08.004

    Article  Google Scholar 

  64. Messick, S.: The nature of cognitive styles: problems and promise in educational practice. Educ. Psychol. 19, 59–74 (1984)

    Article  Google Scholar 

  65. Milani, F., Dumas, M., Ahmed, N., Matulevičius, R.: Modelling families of business process variants: a decomposition driven method. Inf. Syst. (2013). https://doi.org/10.1016/j.is.2015.09.003

    Article  Google Scholar 

  66. Mindock, J., Watney, G.: Integrating system and software engineering through modeling. In: 2008 IEEE Aerospace Conference, pp. 1–12. IEEE (2008)

  67. Mohagheghi, P., Dehlen, V.: Where is the proof?—A review of experiences from applying mde in industry. In: Schieferdecker, I., Hartman, A. (eds.) Model Driven Architecture—Foundations and Applications. Lecture Notes in Computer Science, vol. 5095, pp. 432–443. Springer, Berlin Heidelberg (2008)

  68. Mohagheghi, P., Gilani, W., Stefanescu, A., Fernandez, M.A., Nordmoen, B., Fritzsche, M.: Where does model-driven engineering help? experiences from three industrial cases. Softw. Syst. Model. 12(3), 619–639 (2013)

    Article  Google Scholar 

  69. Moody, D.: The “physics’’ of notations: Toward a scientific basis for constructing visual notations in software engineering. IEEE Trans. Softw. Eng. 35(6), 756–779 (2009). https://doi.org/10.1109/TSE.2009.67

    Article  Google Scholar 

  70. Nguyen, P.H., Klein, J., Le Traon, Y., Kramer, M.E.: A systematic review of model-driven security. In: 2013 20th Asia-Pacific Software Engineering Conference (APSEC), vol. 1, pp. 432–441. IEEE (2013)

  71. Nguyen, P.H., Kramer, M., Klein, J., Le Traon, Y.: An extensive systematic review on the model-driven development of secure systems. Inf. Softw. Technol. 68, 62–81 (2015)

    Article  Google Scholar 

  72. Petersen, K., Feldt, R., Mujtaba, S., Mattsson, M.: Systematic mapping studies in software engineering. In: Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering, p. 17 (2008)

  73. Petersen, K., Vakkalanka, S., Kuzniarz, L.: Guidelines for conducting systematic mapping studies in software engineering: an update. Inf. Softw. Technol. 64, 1–18 (2015). https://doi.org/10.1016/j.infsof.2015.03.007

    Article  Google Scholar 

  74. Pinggera, J., Soffer, P., Fahland, D., Weidlich, M., Zugal, S., Weber, B., Reijers, H., Mendling, J.: Styles in business process modeling: an exploration and a model. Softw. Syst. Model. (2013). https://doi.org/10.1007/s10270-013-0349-1

    Article  Google Scholar 

  75. Pinggera, J., Soffer, P., Zugal, S., Weber, B., Weidlich, M., Fahland, D., Reijers, H.A., Mendling, J.: Modeling styles in business process modeling. In: Bider, I., Halpin, T., Krogstie, J., Nurcan, S., Proper, E., Schmidt, R., Soffer, P., Wrycza, S. (eds.) Enterprise, Business-Process and Information Systems Modeling, pp. 151–166. Springer, Berlin Heidelberg, Berlin, Heidelberg (2012)

    Chapter  Google Scholar 

  76. Reggio, G., Leotta, M., Ricca, F., Astesiano, E.: Business process modelling: five styles and a method to choose the most suitable one. In: Proceedings of the Second Edition of the International Workshop on Experiences and Empirical Studies in Software Modelling, EESSMod ’12. Association for Computing Machinery, New York, NY, USA (2012). https://doi.org/10.1145/2424563.2424574

  77. Rivera, L.F., Müller, H.A., Villegas, N.M., Tamura, G., Jiménez, M.: On the engineering of iot-intensive digital twin software systems. In: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops, pp. 631–638 (2020)

  78. Rolland, C., Souveyet, C., Achour, C.: Guiding goal modeling using scenarios. IEEE Trans. Softw. Eng. TSE (1999). https://doi.org/10.1109/32.738339

    Article  Google Scholar 

  79. Rumbaugh, J., Blaha, M., Premerlani, W., Eddy, F., Lorensen, W.E., et al.: Object-Oriented Modeling and Design, vol. 199. Prentice-hall Englewood Cliffs, NJ (1991)

    Google Scholar 

  80. Runeson, P., Höst, M., Rainer, A., Regnell, B.: Case study research in software engineering—guidelines and examples (2012)

  81. Saini, R., Mussbacher, G., Guo, J.L., Kienzle, J.: Automated, interactive, and traceable domain modelling empowered by artificial intelligence. Softw. Syst. Model. 1–31 (2022)

  82. Santos, M., Gralha, C., Goulão, M., Araújo, J.: Increasing the semantic transparency of the kaos goal model concrete syntax. In: Trujillo, J.C., Davis, K.C., Du, X., Li, Z., Ling, T.W., Li, G., Lee, M.L. (eds.) Conceptual Modeling, pp. 424–439 (2018)

  83. Santos, M., Gralha, C., Goulão, M., Araújo, J., Moreira, A.: On the impact of semantic transparency on understanding and reviewing social goal models. In: 2018 IEEE 26th International Requirements Engineering Conference (RE), pp. 228–239 (2018). https://doi.org/10.1109/RE.2018.00031

  84. Schätz, B., Törngreen, M., Bensalem, S., Cengarle, M.V., Pfeifer, H., McDermid, J., Passerone, R., Sangiovanni-Vincentelli, A.L.: Cyber-physical european roadmap and strategy: research agenda and recommendations for action. CyPhERS . Tech. Rep (2015)

  85. Schuette, R., Rotthowe, T.: The guidelines of modeling – an approach to enhance the quality in information models. In: Ling, T.W., Ram, S., Li Lee, M. (eds.) Conceptual Modeling – ER ’98, pp. 240–254. Springer Berlin Heidelberg, Berlin, Heidelberg (1998)

  86. Soffer, P., Kaner, M., Wand, Y.: Towards understanding the process of process modeling: theoretical and empirical considerations. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) Business Process Management Workshops, pp. 357–369. Springer, Berlin, Heidelberg (2012)

    Chapter  Google Scholar 

  87. Somogyi, F.A., Asztalos, M.: Systematic review of matching techniques used in model-driven methodologies. Softw. Syst. Model. 19(3), 693–720 (2020)

    Article  Google Scholar 

  88. Sousa, K., Mendonça, H., Vanderdonckt, J., Rogier, E., Vandermeulen, J.: User interface derivation from business processes: a model-driven approach for organizational engineering. In: Proceedings of the 2008 ACM symposium on Applied computing, pp. 553–560 (2008)

  89. Störrle, H.: On the impact of layout quality to understanding uml diagrams: Size matters. In: Dingel, J., Schulte, W., Ramos, I., Abrahão, S., Insfran, E. (eds.) Model-Driven Engineering Languages and Systems, pp. 518–534 (2014)

  90. Störrle, H.: Diagram size vs. layout flaws: understanding quality factors of uml diagrams. In: Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM ’16, pp. 31:1–31:10 (2016)

  91. Störrle, H.: On the impact of size to the understanding of uml diagrams. Softw. Syst. Model. 17(1), 115–134 (2018). https://doi.org/10.1007/s10270-016-0529-x

    Article  Google Scholar 

  92. Störrle, H., Fish, A.: Towards an operationalization of the “physics of notations’’ for the analysis of visual languages. In: Moreira, A., Schätz, B., Gray, J., Vallecillo, A., Clarke, P. (eds.) Model-Driven Engineering Languages and Systems, pp. 104–120. Springer, Berlin, Heidelberg (2013)

    Chapter  Google Scholar 

  93. Sunkle, S., Saxena, K., Patil, A., Kulkarni, V.: Ai-driven streamlined modeling: experiences and lessons learned from multiple domains. Softw. Syst. Model. 21(3), 1–23 (2022)

    Article  PubMed  PubMed Central  Google Scholar 

  94. Sutter, H., Alexandrescu, A.: C++ coding standards: 101 rules, guidelines, and best practices. Pearson Education (2004)

  95. Wang, Z.: A modeling approach for use-cases model in uml. In: 2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI), pp. 176–179 (2012). https://doi.org/10.1109/ICACI.2012.6463145

  96. Weyssow, M., Sahraoui, H., Syriani, E.: Recommending metamodel concepts during modeling activities with pre-trained language models. Softw. Syst. Model. 21(3), 1071–1089 (2022)

    Article  Google Scholar 

  97. Whittle, J., Hutchinson, J., Rouncefield, M., Burden, H., Heldal, R.: Industrial adoption of model-driven engineering: Are the tools really the problem? In: Moreira, A., Schätz, B., Gray, J., Vallecillo, A., Clarke, P. (eds.) Model-Driven Engineering Languages and Systems. Lecture Notes in Computer Science, vol. 8107, pp. 1–17. Springer, Berlin Heidelberg (2013)

  98. Wieringa, R., Maiden, N., Mead, N., Rolland, C.: Requirements engineering paper classification and evaluation criteria: a proposal and a discussion. Requir. Eng. 11, 102–107 (2006). https://doi.org/10.1007/s00766-005-0021-6

    Article  Google Scholar 

  99. Wohlin, C.: Guidelines for snowballing in systematic literature studies and a replication in software engineering. In: Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering, EASE ’14. Association for Computing Machinery, New York, NY, USA (2014). https://doi.org/10.1145/2601248.2601268

  100. Wu, J., Yue, T., Ali, S., Zhang, H.: A modeling methodology to facilitate safety-oriented architecture design of industrial avionics software. Softw. Pract. Exp. (2015). https://doi.org/10.1002/spe.2281

    Article  Google Scholar 

  101. Zhang, L., Tian, J.H., Jiang, J., Liu, Y.J., Pu, M.Y., Yue, T.: Empirical research in software engineering–a literature survey. J. Comput. Sci. Technol. (2018). https://doi.org/10.1007/s11390-018-1864-x

    Article  Google Scholar 

  102. Zhao, X., Gray., J.: Design guidelines for feature model construction: Exploring the relationship between feature model structure and structural complexity. In: Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development - MODELSWARD, pp. 325–333. INSTICC, SciTePress (2019). https://doi.org/10.5220/0007388703250333

  103. Zheng, C., Le Duigou, J., Bricogne, M., Eynard, B.: Multidisciplinary interface model for design of mechatronic systems. Comput. Ind. 76, 24–37 (2016)

    Article  Google Scholar 

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  1. Reykjavik University, Menntavegur 1, 102, Reykjavík, Iceland

    Shalini Chakraborty & Grischa Liebel

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  1. Shalini Chakraborty
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Paper categorisation details

Paper categorisation details

In the following, we list the papers we used during our analysis. Table 7 shows the papers extracted during the original search, while Table 8 shows the papers from the snowball search.

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Chakraborty, S., Liebel, G. Modelling guidance in software engineering: a systematic literature review. Softw Syst Model 23, 249–265 (2024). https://doi.org/10.1007/s10270-023-01117-1

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