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A Quantitative Assessment Method for Microservices Granularity to Improve Maintainability

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Enterprise Design, Operations, and Computing. EDOC 2023 Workshops (EDOC 2023)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 498))

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Abstract

The popularity of microservices has increased over the past decade due to their potential benefits for distributed enterprise applications. Developing and maintaining a microservices architecture (MSA) is challenging, amongst others because the size (granularity) of the microservices has an impact on most system properties, such as, e.g., maintainability, performance, and scalability. Currently, architects determine the granularity of the microservices by identifying bounded contexts or business capabilities, which is mainly based on their experience. This paper presents a quantitative assessment method to evaluate the granularity of the microservices for improved system maintainability. The method is based on a set of metrics that are relevant for maintainability, namely change coupling, structural coupling, weighted service interface count, lines of code, service interface data cohesion, and change frequency. By evaluating these metrics, focusing on coupling, cohesion, and size, the method can assess refactors of an architecture in which microservices are merged or decomposed. We validated our method with three open source microservice-based projects with different sizes and structures. Our method can substantiate the design decisions concerning the granularity of microservices, identifying services that are candidates for merging and decomposition towards maintainability evolution, with clear benefits particularly for enterprise applications.

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Notes

  1. 1.

    https://github.com/famkedriessen/quantitative-assessment-method-for-microservices-granularity.

References

  1. Aboalkheir, A.: Ultimate list of Version Control Systems statistics, trends (2023). https://abdalslam.com/version-control-systems-statistics. Accessed 15 Aug 2023

  2. Alshuqayran, N., Ali, N., Evans, R.: Towards micro service architecture recovery: an empirical study. In: 2018 IEEE International Conference on Software Architecture (ICSA), pp. 47–4709 (2018). https://doi.org/10.1109/ICSA.2018.00014

  3. Apolinário, D.R., de França, B.B.: A method for monitoring the coupling evolution of microservice-based architectures. J. Braz. Comput. Soc. 27, 1–35 (2021). https://doi.org/10.1186/s13173-021-00120-y

  4. Athanasopoulos, D., Zarras, A.V., Miskos, G., Issarny, V., Vassiliadis, P.: Cohesion-driven decomposition of service interfaces without access to source code. IEEE Trans. Serv. Comput. 8(4), 550–562 (2015). https://doi.org/10.1109/TSC.2014.2310195

    Article  Google Scholar 

  5. Bogner, J., Schlinger, S., Wagner, S., Zimmermann, A.: A modular approach to calculate service-based maintainability metrics from runtime data of microservices. In: Franch, X., Männistö, T., Martínez-Fernández, S. (eds.) PROFES 2019. LNCS, vol. 11915, pp. 489–496. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-35333-9_34

    Chapter  Google Scholar 

  6. Bogner, J., Wagner, S., Zimmermann, A.: Automatically measuring the maintainability of service- and microservice-based systems - a literature review. In: Proceedings of the 27th International Workshop on Software Measurement and 12th International Conference on Software Process and Product Measurement, IWSM-Mensura 2017, pp. 107–115. ACM (2017). https://doi.org/10.1145/3143434.3143443

  7. Bogner, J., Wagner, S., Zimmermann, A.: Collecting service-based maintainability metrics from RESTful API descriptions: static analysis and threshold derivation. In: Muccini, H., et al. (eds.) ECSA 2020. CCIS, vol. 1269, pp. 215–227. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-59155-7_16

    Chapter  Google Scholar 

  8. Cardarelli, M., Salle, A.D., Iovino, L., Malavolta, I., Francesco, P.D., Lago, P.: An extensible data-driven approach for evaluating the quality of microservice architectures. In: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, pp. 1225–1234. ACM (2019). https://doi.org/10.1145/3297280.3297400

  9. Evans, E.: Domain-Driven Design: Tackling Complexity in the Heart of Software. Addison-Wesley (2004)

    Google Scholar 

  10. Granchelli, G., Cardarelli, M., Di Francesco, P., Malavolta, I., Iovino, L., Di Salle, A.: MicroART: a software architecture recovery tool for maintaining microservice-based systems. In: 2017 IEEE International Conference on Software Architecture Workshops (ICSAW), pp. 298–302 (2017). https://doi.org/10.1109/ICSAW.2017.9

  11. Granchelli, G., Cardarelli, M., Di Francesco, P., Malavolta, I., Iovino, L., Di Salle, A.: Towards recovering the software architecture of microservice-based systems. In: 2017 IEEE International Conference on Software Architecture Workshops (ICSAW), pp. 46–53 (2017). https://doi.org/10.1109/ICSAW.2017.48

  12. Heitlager, I., Kuipers, T., Visser, J.: A practical model for measuring maintainability. In: Proceedings of the 6th International Conference on Quality of Information and Communications Technology, pp. 30–39 (2007)

    Google Scholar 

  13. Hirzalla, M., Cleland-Huang, J., Arsanjani, A.: A metrics suite for evaluating flexibility and complexity in service oriented architectures. In: Feuerlicht, G., Lamersdorf, W. (eds.) ICSOC 2008. LNCS, vol. 5472, pp. 41–52. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-01247-1_5

    Chapter  Google Scholar 

  14. Homay, A., de Sousa, M., Zoitl, A., Wollschlaeger, M.: Service granularity in industrial automation and control systems. In: 25th IEEE International Conference on Emerging Technologies and Factory Automation, vol. 1, pp. 132–139 (2020)

    Google Scholar 

  15. IBM Market Development & Insights Team: Microservices in the enterprise, 2021: Real benefits, worth the challenges (2021). https://www.ibm.com/downloads/cas/OQG4AJAM

  16. Li, Y., Wang, C.Z., Li, Y.C., Su, J., Chen, C.H.: Granularity decision of microservice splitting in view of maintainability and its innovation effect in government data sharing. Discrete Dynamics in Nature and Society 2020 (2020). https://doi.org/10.1155/2020/1057902

  17. Oliva, G.A., Gerosa, M.A.: Chapter 11 - Change coupling between software artifacts: learning from past changes. In: Bird, C., Menzies, T., Zimmermann, T. (eds.) The Art and Science of Analyzing Software Data, pp. 285–323. Morgan Kaufmann, Boston (2015)

    Chapter  Google Scholar 

  18. Panichella, S., Rahman, M.I., Taibi, D.: Structural coupling for microservices. In: Proceedings of the 11th International Conference on Cloud Computing and Services Science (CLOSER 2021), pp. 280–287. SCITEPRESS (2021). https://doi.org/10.5220/0010481902800287

  19. Rahman, M.I., Panichella, S., Taibi, D.: A curated dataset of microservices-based systems. In: Joint Proceedings of the Summer School on Software Maintenance and Evolution. CEUR-WS 2520 (2019)

    Google Scholar 

  20. Tornhill, A.: Your Code as a Crime Scene. Pragmatic Bookshelf (2015)

    Google Scholar 

  21. Vera-Rivera, F.H., Gaona, C., Astudillo, H.: Defining and measuring microservice granularity-a literature overview. PeerJ Comput. Sci. 7, e695 (2021). https://doi.org/10.7717/peerj-cs.695

  22. Zimmermann, O.: Microservices tenets: agile approach to service development and deployment. Comput. Sci. - Res. Dev. 32, 301–310 (2017). https://doi.org/10.1007/s00450-016-0337-0

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Author information

Authors and Affiliations

  1. Semantics, Cybersecurity and Services group, University of Twente, PO Box 127, 7500 AE, Enschede, The Netherlands

    Luís Ferreira Pires & João Luiz Rebelo Moreira

  2. Deloitte Consulting, P.O. Box 58110, 1040 HC, Amsterdam, The Netherlands

    Famke Driessen, Paul Verhoeven & Sander van den Bosch

Authors
  1. Famke Driessen
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  2. Luís Ferreira Pires
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  3. João Luiz Rebelo Moreira
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  4. Paul Verhoeven
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  5. Sander van den Bosch
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Corresponding author

Correspondence to Famke Driessen .

Editor information

Editors and Affiliations

  1. University of Twente, Enschede, The Netherlands

    Tiago Prince Sales

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Sybren de Kinderen

  3. Vienna University of Technology, Vienna, Austria

    Henderik A. Proper

  4. Technical University of Munich, Heilbronn, Germany

    Luise Pufahl

  5. University of Groningen, Groningen, The Netherlands

    Dimka Karastoyanova

  6. University of Twente, Enschede, The Netherlands

    Marten van Sinderen

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Driessen, F., Ferreira Pires, L., Moreira, J.L.R., Verhoeven, P., van den Bosch, S. (2024). A Quantitative Assessment Method for Microservices Granularity to Improve Maintainability. In: Sales, T.P., de Kinderen, S., Proper, H.A., Pufahl, L., Karastoyanova, D., van Sinderen, M. (eds) Enterprise Design, Operations, and Computing. EDOC 2023 Workshops . EDOC 2023. Lecture Notes in Business Information Processing, vol 498. Springer, Cham. https://doi.org/10.1007/978-3-031-54712-6_13

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  • DOI: https://doi.org/10.1007/978-3-031-54712-6_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-54711-9

  • Online ISBN: 978-3-031-54712-6

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