Decision-making on Command Query Responsibility Segregation with Event Sourcing architectural variations

Authors

DOI:

https://doi.org/10.15587/2706-5448.2025.337168

Keywords:

software architectures, software metrics, formal methods, support decision-making, CQRS, Event Sourcing

Abstract

The object of the research is the process of selecting and evaluating architectural solutions, both at the design stage and during the migration of a software application’s architecture, within the context of evolutionary architecture. The paper is focused on variations of the Command Query Responsibility Segregation (CQRS) with Event Sourcing (ES) architecture, which, in fact, is a family of architectural variations that differ in complexity, performance, development time, and the required expertise from developers. These differences have a significant impact on the development cost and maintainability of the software application. Moreover, changes in business requirements or technical context often necessitate migration among architectural variations, which may drastically increase costs if not planned properly.

In the absence of objective evaluation criteria, decisions are often based on expert judgment, which may be unavailable or insufficient. This work proposes a decision-making support approach for CQRS with ES architectural variation selection and migration planning. The approach is based on classification of processes and breaking them down into smaller activities. This enables objective comparisons of architectural variations based on complexity and performance metrics.

The application of the approach is shown on two basic variations. Metrics were obtained, and a bitmap chart was built to visualize architectural applicability, depending on the project priorities. The applicability score of mCQRS ranges from 39% to 53%, while that of Classical CQRS – 47–61%.

The proposed approach is applicable in projects where architecture evolution is expected. It is especially useful in organizations operating at Capability Maturity Models Integration (CMMI) Level 4 (Quantitatively Managed Organization) which is focused on predictability of quantitative performance improvement objectives.

Author Biographies

Oleksandr Lytvynov, Oles Honchar Dnipro National University

PhD, Associate Professor

Department of Electronic Computing Machinery

Dmytro Hruzin, Oles Honchar Dnipro National University

PhD Student

Department of Electronic Computing Machinery

References

  1. Fowler, M., Rice, D., Foemmel, M., Hieatt, E., Mee, R., Stafford, R. (2002). Patterns of Enterprise Application Architecture. Boston: Addison-Wesley, 560. Available at: https://dl.ebooksworld.ir/motoman/Patterns%20of%20Enterprise%20Application%20Architecture.pdf
  2. Hohpe, G., Woolf, B. (2011). Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions. Boston: Addison-Wesley. Available at: https://ptgmedia.pearsoncmg.com/images/9780321200686/samplepages/0321200683.pdf
  3. Evans, E. (2003). Domain-Driven Design: Tackling Complexity in the Heart of Software. Boston: Addison-Wesley. Available at: https://fabiofumarola.github.io/nosql/readingMaterial/Evans03.pdf
  4. Zhong, Y., Li, W., Wang, J. (2019). Using Event Sourcing and CQRS to Build a High Performance Point Trading System. Proceedings of the 2019 5th International Conference on E-Business and Applications. Bangkok, New York, 16–19. https://doi.org/10.1145/3317614.3317632
  5. Betts, D., Dominguez, J., Melnik, G., Simonazzi, F., Subramanian, M. (2012). Exploring CQRS and Event Sourcing: A Journey into High Scalability, Availability, and Maintainability with Windows Azure. Microsoft patterns & practices. Available at: https://download.microsoft.com/download/e/a/8/ea8c6e1f-01d8-43ba-992b-35cfcaa4fae3/cqrs_journey_guide.pdf
  6. Fowler, M. (2011). CQRS. Available at: https://martinfowler.com/bliki/CQRS.html
  7. Young, G. (2010). CQRS Documents by Greg Young. Available at: https://cqrs.files.wordpress.com/2010/11/cqrs_documents.pdf
  8. Young, G. (2017). Event Centric: Finding Simplicity in Complex Systems. Boston: Addison-Wesley Professional, 560.
  9. Taylor, H., Yochem, A., Phillips, L., Martinez, F. (2009). Event-Driven Architecture: How SOA Enables the RealTime Enterprise. Boston: Addison-Wesley, 272.
  10. Vernon, V. (2013). Implementing Domain-Driven Design. Boston: Addison Wesley, 656.
  11. Ford, N., Parsons, R., Kua, P., Sadalage, P. (2022). Building evolutionary architectures. Sebastopol: O'Reilly Media, 262.
  12. Event Sourcing pattern. Microsoft. Available at: https://learn.microsoft.com/en-us/azure/architecture/patterns/event-sourcing
  13. Comartin, D. (2021). Snapshots in Event Sourcing for Rehydrating Aggregates. CodeOpinion. Available at: https://codeopinion.com/snapshots-in-event-sourcing-for-rehydrating-aggregates/
  14. Evsyukov, O. (2020). Bermudskyi Ahrehat. I spasenye utopaiushchykh. Domain-Driven Design Injection. Available at: https://youtu.be/Br4TL-486ZM?t=1500
  15. Young, G. (2017). Versioning in an Event Sourced System. Available at: https://leanpub.com/esversioning/read
  16. Kleanthous, S. (2021). Event immutability and dealing with change. Kurrent. Available at: https://www.eventstore.com/blog/event-immutability-and-dealing-with-change
  17. Zheng, Z., Xie, S., Dai, H., Chen, X., Wang, H. (2017). An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends. 2017 IEEE International Congress on Big Data (BigData Congress). Honolulu, 557–564. https://doi.org/10.1109/bigdatacongress.2017.85
  18. Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) (Text with EEA relevance). Official Journal of the European Union, 119, 4.5.2016, 1–88. Available at: https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng
  19. Vasconcellos, P. R. G., Bezerra, V. M., Bianchini, C. P. (2018). Applying Event Sourcing in a ERP System: A Case Study. 2018 XLIV Latin American Computer Conference (CLEI). São Paulo, 80–89. https://doi.org/10.1109/clei.2018.00019
  20. Korkmaz, N., Nilsson, M. (2014). Practitioners’ view on command query responsibility segregation. [Master's thesis; Lund University]. Available at: https://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=4864802&fileOId=4864803
  21. Lytvynov, O., Hruzin, D., Frolov, M. (2024). On the migration of domain driven design to CQRS with event sourcing software architecture. Information Technology: Computer Science, Software Engineering and Cyber Security, 1, 50–60. https://doi.org/10.32782/it/2024-1-7
  22. Pandiya, D. K., Charankar, N. G. (2024). Optimizing Performance and Scalability in Micro Services with CQRS Design. International Journal of Engineering Research & Technology, 13 (4). Available at: https://www.ijert.org/optimizing-performance-and-scalability-in-micro-services-with-cqrs-design
  23. DBB Software's. Available at: https://dbbsoftware.com/
  24. ISO/IEC/IEEE 24748-1:2024(en) Systems and software engineering – Life cycle management – Part 1: Guidelines for life cycle management (2024). ISO. Available at: https://www.iso.org/obp/ui/en/#iso:std:iso-iec-ieee:24748:-1:ed-2:v1:en
  25. Sobhy, D., Bahsoon, R., Minku, L., Kazman, R. (2021). Evaluation of Software Architectures under Uncertainty. ACM Transactions on Software Engineering and Methodology, 30 (4), 1–50. https://doi.org/10.1145/3464305
  26. Bahsoon, R., Emmerich, W. (2003). Evaluating software architectures: development, stability, and evolution. ACS/IEEE International Conference on Computer Systems and Applications. Tunis, 47. https://doi.org/10.1109/aiccsa.2003.1227480
  27. Kazman, R., Bass, L., Abowd, G., Webb, M. (1994). SAAM: a method for analyzing the properties of software architectures. Proceedings of 16th International Conference on Software Engineering. Sorrento, 81–90. https://doi.org/10.1109/icse.1994.296768
  28. Kazman, R., Klein, M., Clements, P. (2000). ATAM: Method for Architecture Evaluation. Technical report CMU/SEI-2000-TR-004. Carnegie Mellon Software Engineering Institute. Pittsburgh. Available at: https://www.sei.cmu.edu/documents/629/2000_005_001_13706.pdf
  29. Kazman, R., Jai Asundi, Klein, M. (2001). Quantifying the costs and benefits of architectural decisions. Proceedings of the 23rd International Conference on Software Engineering. ICSE 2001. Toronto, 297–306. https://doi.org/10.1109/icse.2001.919103
  30. Faniyi, F., Bahsoon, R., Evans, A., Kazman, R. (2011). Evaluating Security Properties of Architectures in Unpredictable Environments: A Case for Cloud. 2011 Ninth Working IEEE/IFIP Conference on Software Architecture. Washington, 127–136. https://doi.org/10.1109/wicsa.2011.25
  31. Zarghami, M., Szidarovszky, F. (2011). Introduction to Multicriteria Decision Analysis. Multicriteria Analysis. Berlin, Heidelberg: Springer, 1–12. https://doi.org/10.1007/978-3-642-17937-2_1
  32. Brunelli, M. (2015). Introduction to the Analytic Hierarchy Process. SpringerBriefs in Operations Research. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-12502-2
  33. Al-Naeem, T., Gorton, I., Babar, M. A., Rabhi, F., Benatallah, B. (2005). A quality-driven systematic approach for architecting distributed software applications. Proceedings of the 27th International Conference on Software Engineering – ICSE ’05. St. Louis, 244–253. https://doi.org/10.1145/1062455.1062508
  34. Kim, C.-K., Lee, D.-H., Ko, I.-Y., Baik, J. (2007). A Lightweight Value-based Software Architecture Evaluation. Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007). Washington, 646–649. https://doi.org/10.1109/snpd.2007.507
  35. Bourque, P., Fairley, R. E. (2014). Guide to the Software Engineering Body of Knowledge – SWEBOK V3.0. Piscataway: IEEE and IEEE Computer Society Press. Available at: https://www.researchgate.net/publication/342452008_Guide_to_the_Software_Engineering_Body_of_Knowledge_-_SWEBOK_V30
  36. Nivedhaa, N. (2024). Software architecture evolution: Patterns, trends, and best practices. International Journal of Computer Sciences and Engineering, 1, 1–14. Available at: https://www.researchgate.net/publication/384019495_SOFTWARE_ARCHITECTURE_EVOLUTION_PATTERNS_TRENDS_AND_BEST_PRACTICES
  37. Milić, M., Makajić-Nikolić, D. (2022). Development of a Quality-Based Model for Software Architecture Optimization: A Case Study of Monolith and Microservice Architectures. Symmetry, 14 (9), 1824. https://doi.org/10.3390/sym14091824
  38. ISO/IEC/IEEE 24765:2017 Systems and software engineering – Vocabulary (2017). ISO. Available at: https://www.iso.org/standard/71952.html
  39. Mohapatra, S. K., Prasad, S. (2015). Finding Representative Test Case for Test Case Reduction in Regression Testing. International Journal of Intelligent Systems and Applications, 7 (11), 60–65. https://doi.org/10.5815/ijisa.2015.11.08
  40. Mens, T. (2016). Research trends in structural software complexity. arXiv:1608.01533v1. https://doi.org/10.48550/arXiv.1608.01533
  41. Sarala, S., Abdul Jabbar, P. (2010). Information flow metrics and complexity measurement. 2010 3rd International Conference on Computer Science and Information Technology. Chengdu, 575–578. https://doi.org/10.1109/iccsit.2010.5563667
  42. Beyer, D., Häring, P. (2014). A formal evaluation of DepDegree based on weyuker’s properties. Proceedings of the 22nd International Conference on Program Comprehension. Hyderabad, 258–261. https://doi.org/10.1145/2597008.2597794
  43. McCabe, T. J. (1976). A Complexity Measure. IEEE Transactions on Software Engineering, SE-2 (4), 308–320. https://doi.org/10.1109/tse.1976.233837
  44. Halstead, M. H. (1977). Elements of Software Science. New York: Elsevier Science Inc., 128.
  45. Stepien, B. (2003). Software development cost estimation methods and research trends. Computer Science, 5 (1), 67–86. Available at: https://www.researchgate.net/publication/50365764_Software_Development_Cost_Estimation_Methods
  46. Wang, Y., Shao, J. (2003). Measurement of the cognitive functional complexity of software. Proceedings of the 2nd IEEE International Conference on Cognitive Informatics (ICCI '03). Washington, 67–74. https://doi.org/10.1109/COGINF.2003.1225955
  47. Zlaugotne, B., Zihare, L., Balode, L., Kalnbalkite, A., Khabdullin, A., Blumberga, D. (2020). Multi-Criteria Decision Analysis Methods Comparison. Environmental and Climate Technologies, 24 (1), 454–471. https://doi.org/10.2478/rtuect-2020-0028
  48. Jahanshahi, H., Alijani, Z., Mihalache, S. F. (2023). Towards Sustainable Transportation: A Review of Fuzzy Decision Systems and Supply Chain Serviceability. Mathematics, 11 (8), 1934. https://doi.org/10.3390/math11081934
  49. Vafaei, N., Ribeiro, R. A., Camarinha-Matos, L. M. (2016). Normalization Techniques for Multi-Criteria Decision Making: Analytical Hierarchy Process Case Study. Technological Innovation for Cyber-Physical Systems. Costa de Caparica, 261–269. https://doi.org/10.1007/978-3-319-31165-4_26
  50. Young, G. (2023). GitHub: EventStore repository. Available at: https://github.com/gregoryyoung/EventStore
  51. Driscoll, M. (2017). The Publish-Subscribe Pattern. WxPython Recipes. Berkeley: Apress, 43–50. https://doi.org/10.1007/978-1-4842-3237-8_4
  52. CQRS. Practical and focused guide for survival in post-CQRS world: Projections. Available at: http://cqrs.wikidot.com/doc:projection
  53. Hierons, R. M., Türker, U. C. (2017). Parallel Algorithms for Generating Distinguishing Sequences for Observable Non-deterministic FSMs. ACM Transactions on Software Engineering and Methodology, 26 (1), 1–34. https://doi.org/10.1145/3051121
  54. Wang, J., Tepfenhart, W. (2019). Petri Nets. Formal Methods in Computer Science. Chapman and Hall, CRC, 201–243. https://doi.org/10.1201/9780429184185-8
  55. Bollig, B., Katoen, J.-P., Kern, C., Leucker, M. (2010). Learning Communicating Automata from MSCs. IEEE Transactions on Software Engineering, 36 (3), 390–408. https://doi.org/10.1109/tse.2009.89
  56. Brand, D., Zafiropulo, P. (1983). On Communicating Finite-State Machines. Journal of the ACM, 30 (2), 323–342. https://doi.org/10.1145/322374.322380
  57. Harel, D. (1987). Statecharts: a visual formalism for complex systems. Science of Computer Programming, 8 (3), 231–274. https://doi.org/10.1016/0167-6423(87)90035-9
  58. Booch, G., Rumbaugh, J., Jacobson, I. (1999). The Unified Modeling Language User Guide. Addison Wesley Longman Publishing Co., Inc., 512. Available at: https://patologia.com.mx/informatica/uug.pdf
  59. Alur, R., Etessami, K., Yannakakis, M. (2001). Analysis of Recursive State Machines. Computer Aided Verification. Berlin, Heidelberg: Springer-Verlag, 207–220. https://doi.org/10.1007/3-540-44585-4_18
  60. Alur, R., Benedikt, M., Etessami, K., Godefroid, P., Reps, T., Yannakakis, M. (2005). Analysis of recursive state machines. ACM Transactions on Programming Languages and Systems, 27 (4), 786–818. https://doi.org/10.1145/1075382.1075387
  61. Chatterjee, K., Kragl, B., Mishra, S., Pavlogiannis, A. (2017). Faster algorithms for weighted recursive state machines. Proceedings of the 26th European Symposium on Programming, ESOP 2017 held as Part of the European Joint Conferences on Theory and Practice of Software. Uppsala: Springer, 287–313. https://doi.org/10.48550/arXiv.1701.04914
  62. Dubslaff, C., Wienhöft, P., Fehnker, A. (2024). Lazy model checking for recursive state machines. Software and Systems Modeling, 23 (2), 369–401. https://doi.org/10.1007/s10270-024-01159-z
  63. Simon, E., Stoffel, K. (2009). State machines and petri nets as a formal representation for systems life cycle management. Proceedings of the International Conference Information Systems. Barcelona, 275–282. Available at: https://www.researchgate.net/publication/228721890_State_machines_and_petri_nets_as_a_formal_representation_for_systems_life_cycle_management
  64. Van Der Aalst, W. M. P. (1998). The Application of Petri Nets to Workflow Management. Journal of Circuits, Systems and Computers, 8 (1), 21–66. https://doi.org/10.1142/s0218126698000043
  65. Jensen, K. (1996). Coloured Petri Nets. Monographs in Theoretical Computer Science. An EATCS Series. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-662-03241-1
  66. Ullman, J. D. (1998). Elements of ML Programming. New Jersey: Prentice-Hall. Available at: https://www.scribd.com/doc/221508984/Elements-of-Ml-Programming
  67. Fehling, R. (1993). A concept of hierarchical Petri nets with building blocks. Advances in Petri Nets 1993, 148–168. https://doi.org/10.1007/3-540-56689-9_43
  68. Farwer, B., Misra, K. (2002). Modelling with hierarchical object Petri nets. Fundamenta Informaticae, 55 (2), 129–147. Available at: https://www.researchgate.net/publication/220445187_Modelling_with_Hierarchical_Object_Petri_Nets
  69. Chistikov, D., Czerwinski, W., Hofman, P., Mazowiecki, F., Sinclair-Banks, H. (2023). Acyclic Petri and Workflow Nets with Resets. Proceedings of the 43rd IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science. Dagstuhl Castle, Leibniz Center for Informatics, 284, 1–18. https://doi.org/10.4230/LIPIcs.FSTTCS.2023.16
  70. Lomazova, I. A., Mitsyuk, A. A., Rivkin, A. (2021). Soundness in Object-centric Workflow Petri Nets. arXiv:2112.14994v1. https://doi.org/10.48550/arXiv.2112.14994
  71. Blondin, M., Mazowiecki, F., Offtermatt, P. (2022). The complexity of soundness in workflow nets. Proceedings of the 37th Annual ACM/IEEE Symposium on Logic in Computer Science. New York, 1–13. https://doi.org/10.1145/3531130.3533341
  72. Meyer, T. (2023). A Symmetric Petri Net Model of Generic Publish-Subscribe Systems for Verification and Business Process Conformance Checking. Proceedings of the International Workshop on Petri Nets and Software Engineering (PNSE '23). Lisbon: CEUR, Aachen, 88–109. Available at: https://ceur-ws.org/Vol-3430/paper6.pdf
  73. Ding, J., Zhang, D. (2015). Modeling and Analyzing Publish Subscribe Architcture using Petri Nets. Proceedings of the 27th International Conference on Software Engineering and Knowledge Engineering, 2015. Pittsburgh: KSI Research Inc., 589–594. https://doi.org/10.18293/seke2015-232
  74. Genrich, H. J. (1991). Predicate / Transition Nets. High-Level Petri Nets. Berlin, Heidelberg: Springer-Verlag, 3–43. https://doi.org/10.1007/978-3-642-84524-6_1
  75. Lytvynov, O. A., Hruzin, D. L. (2024). Critical causal events in systems based on cqrs with event sourcing architecture. Radio Electronics, Computer Science, Control, 3, 119–143. https://doi.org/10.15588/1607-3274-2024-3-11
  76. Minsky, M. (1974). A Framework for Representing Knowledge. MIT Research Lab Technical Report. Cambridge: Massachusetts Institute of Technology. Available at: https://courses.media.mit.edu/2004spring/mas966/Minsky%201974%20Framework%20for%20knowledge.pdf
  77. Harel, D., Peleg, D. (1985). Process logic with regular formulas. Theoretical Computer Science, 38, 307–322. https://doi.org/10.1016/0304-3975(85)90225-7
  78. Levenshtein, V. (1965). Binary Codes Capable of Correcting Deletions, Insertions, and Reversals. Doklady Akademii nauk SSSR, 10, 707–710. Available at: https://nymity.ch/sybilhunting/pdf/Levenshtein1966a.pdf
  79. Cockburn, A. (2000). Writing Effective Use Cases. Boston: Addison-Wesley Professional, 304. Available at: https://kurzy.kpi.fei.tuke.sk/zsi/resources/CockburnBookDraft.pdf
  80. Hruzin, D. (2025). GitHub: CQRS-variations-test repository. Available at: https://github.com/dmitryhruzin/CQRS-variations-test
  81. Braz, M., Vergilio, S. (2006). Software Effort Estimation Based on Use Cases. 30th Annual International Computer Software and Applications Conference (COMPSAC’06). Chicago, 221–228. https://doi.org/10.1109/compsac.2006.77
  82. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8 (3), 338–353. https://doi.org/10.1016/s0019-9958(65)90241-x
Decision-making on Command Query Responsibility Segregation with Event Sourcing architectural variations

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2025-08-29

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Lytvynov, O., & Hruzin, D. (2025). Decision-making on Command Query Responsibility Segregation with Event Sourcing architectural variations. Technology Audit and Production Reserves, 4(2(84), 37–59. https://doi.org/10.15587/2706-5448.2025.337168

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Vol. 4 No. 2(84) (2025): Information and control systems

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Information Technologies

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