dc.contributor.author | Vera-Rivera, F. H. | |
dc.contributor.author | Puerto Cuadros, Eduard Gilberto | |
dc.contributor.author | Astudillo, Hernán | |
dc.contributor.author | Gaona, Carlos | |
dc.date.accessioned | 2022-12-06T20:45:52Z | |
dc.date.available | 2022-12-06T20:45:52Z | |
dc.date.issued | 2017 | |
dc.identifier.uri | https://repositorio.ufps.edu.co/handle/ufps/6653 | |
dc.description.abstract | The microservice granularity directly affects the quality attributes and usage of computational resources of the system, determining optimal microservice granularity is an open research topic. Microservices granularity is defined by the number of operations exposed by the microservice, the number of microservices that compose the whole application, and its complexity and dependencies. This paper describes "Microservice Backlog (MB)", a semiautomatic model for defining and evaluating the granularity of microservice-based applications; MB uses genetic programming technique to calculate at design time the granularity of each microservice from the user stories in the "product backlog" or release planning; the genetic algorithm combined coupling, cohesion, granularity, semantic similarity, and complexity metrics to define the number of microservices, and the user stories associated with each microservice. MB decomposes the candidate microservices, allowing to analyze graphically the size of each microservice, as well as its complexity, dependencies, coupling, cohesion metrics, and the number of calls or requests between microservices. The resulting decomposition (number of microservices and their granularity) performed by MB shows less coupling, higher cohesion, less complexity, fewer user stories associated with each microservice, and fewer calls among microservices. MB was validated against three existing methods, using two state-of-the-art applications (Cargo Tracking and JPet-Store), and one real-life applications (Foristom Conferences). The development team and/or architect can use metrics to identify the critical points of the system and determine at design time how the microservice-based application will be implemented. | eng |
dc.format.extent | 25 Pàginas | spa |
dc.format.mimetype | application/pdf | spa |
dc.language.iso | eng | spa |
dc.publisher | IEEE Access | spa |
dc.relation.ispartof | IEEE Access.Vol 20. (2017) | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | spa |
dc.source | https://ieeexplore.ieee.org/document/9519691 | spa |
dc.title | Microservices backlog – a genetic programming technique for identification and evaluation of microservices from user stories. | eng |
dc.type | Artículo de revista | spa |
dcterms.references | K. Beck and M. Fowler, Planning Extreme Programming. Addison Wesley, 2001. | spa |
dcterms.references | M. Pikkarainen, J. Haikara, O. Salo, P. Abrahamsson, and J.Still, “The impact of agile practices on communication in software development,” Empir. Softw. Eng., vol. 13, no. 3, pp. 303–337, Jun. 2008, doi: 10.1007/s10664-008-9065-9. | spa |
dcterms.references | Versionone Enterprise, I. Digital.ai Software, and I. CollabNet, “14th annual state of agile report,” 2019. [Online]. Available: www.stateofagile.com | spa |
dcterms.references | T. Sedano, P. Ralph, and C. Peraire, “The Product Backlog,” in Proceedings - International Conference on Software Engineering, May 2019, vol. 2019-May, pp. 200–211, doi: 10.1109/ICSE.2019.00036. | spa |
dcterms.references | A. Balalaie, A. Heydarnoori, and P. Jamshidi, “Microservices Architecture Enables DevOps: Migration to a Cloud-Native Architecture,” IEEE Softw., vol. 33, no. 3, pp. 42–52, 2016, doi: 10.1109/MS.2016.64. | spa |
dcterms.references | O. Zimmermann, “Microservices tenets: Agile approach to service development and deployment,” Comput. Sci. - Res. Dev., vol. 32, no. 3–4, pp. 301–310, 2017, doi: 10.1007/s00450-016-0337-0. | spa |
dcterms.references | P. Jamshidi, C. Pahl, N. C. Mendonca, J. Lewis, and S. Tilkov, “Microservices: The Journey So Far and Challenges Ahead,” IEEE Softw., vol. 35, no. 3, pp. 24–35, May 2018, doi: 10.1109/MS.2018.2141039. | spa |
dcterms.references | S. Hassan, R. Bahsoon, and R. Kazman, “Microservice Transition and its Granularity Problem: A Systematic Mapping Study,” Softw. Pract. Exp., no. February, pp. 1–31, 2020, doi: 10.1002/spe.2869. | spa |
dcterms.references | N. Kulkarni and V. Dwivedi, “The role of service granularity in a successful soa realization - A case study,” in Proceedings - 2008 IEEE Congress on Services, SERVICES 2008, 2008, vol. PART 1, pp. 423–430, doi: 10.1109/SERVICES-1.2008.86. | spa |
dcterms.references | A. Homay, M. de Sousa, A. Zoitl, and M. Wollschlaeger, “Service Granularity in Industrial Automation and Control Systems,” in 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Sep. 2020, pp. 132–139, doi: 10.1109/ETFA46521.2020.9212048. | spa |
dcterms.references | F. H. Vera-Rivera, H. Astudillo, and C. M. Gaona-Cuevas, “Defining and measuring microservice granularity – a literature overview,” PeerJ Comput. Sci., vol. In review | spa |
dcterms.references | F. H. Vera-Rivera, E. G. Puerto-Cuadros, H. Astudillo, and C. M. Gaona-Cuevas, “Microservices Backlog - A Model of Granularity Specification and Microservice Identification,” in International conference on service computing SCC 2020. Lecture Notes in Computer Science, Jun. 2020, vol. 12409 LNCS, pp. 85–102, doi: 10.1007/978-3-030-59592-0_6. | spa |
dcterms.references | M. Gysel, L. Kölbener, W. Giersche, and O. Zimmermann, “Service Cutter: A Systematic Approach to Service Decomposition,” in IFIP International Federation for Information Processing 2016, 2016, pp. 185–200, doi: 10.1007/978-3-319-44482-6_12 | spa |
dcterms.references | C. Richardson and microservices.io, “Microservice Architecture pattern.” https://microservices.io/patterns/microservices.html (accessed Dec. 12, 2019). | spa |
dcterms.references | O. Zimmermann, M. Stocker, U. Zdun, D. Lübke, and C. Pautasso, “Microservice API Patterns,” 2019. https://www.microservice-api-patterns.org/introduction (accessed Dec. 17, 2019). | spa |
dcterms.references | A. Krause, C. Zirkelbach, W. Hasselbring, S. Lenga, and D. Kroger, “Microservice Decomposition via Static and Dynamic Analysis of the Monolith,” Proc. - 2020 IEEE Int. Conf. Softw. Archit. Companion, ICSA-C 2020, pp. 9–16, 2020, doi: 10.1109/ICSA-C50368.2020.00011. | spa |
dcterms.references | O. Al-Debagy and P. Martinek, “Extracting Microservices’ Candidates from Monolithic Applications: Interface Analysis and Evaluation Metrics Approach,” in 2020 IEEE 15th International Conference of System of Systems Engineering (SoSE), Jun. 2020, pp. 289–294, doi: 10.1109/SoSE50414.2020.9130466. | spa |
dcterms.references | W. Jin, T. Liu, Y. Cai, R. Kazman, R. Mo, and Q. Zheng, “Service Candidate Identification from Monolithic Systems based on Execution Traces,” IEEE Trans. Softw. Eng., vol. X, no. X, pp. 1–1, 2019, doi: 10.1109/TSE.2019.2910531. | spa |
dcterms.references | M. Abdullah, W. Iqbal, and A. Erradi, “Unsupervised learning approach for web application auto-decomposition into microservices,” J. Syst. Softw., vol. 151, pp. 243–257, 2019, doi: 10.1016/j.jss.2019.02.031. | spa |
dcterms.references | S. Li et al., “A dataflow-driven approach to identifying microservices from monolithic applications,” J. Syst. Softw., vol. 157, 2019, doi: 10.1016/j.jss.2019.07.008 | spa |
dcterms.references | D. Taibi and K. Syst, “From Monolithic Systems to Microservices: A Decomposition Framework based on Process Mining,” Int. Conf. Cloud Comput. Serv. Sci. - CLOSER 2019, no. March, 2019. | spa |
dcterms.references | N. Santos et al., “A logical architecture design method for microservices architectures,” in ACM International Conference Proceeding Series, Sep. 2019, vol. 2, pp. 145–151, doi: 10.1145/3344948.3344991. | spa |
dcterms.references | O. Al-Debagy and P. Martinek, “A new decomposition method for designing microservices,” Period. Polytech. Electr. Eng. Comput. Sci., vol. 63, no. 4, pp. 274–281, 2019, doi: 10.3311/PPee.13925 | spa |
dcterms.references | A. A. C. De Alwis, A. Barros, C. Fidge, and A. Polyvyanyy, “Business object centric microservices patterns,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11877 LNCS, pp. 476–495, doi: 10.1007/978-3-030-33246-4_30. | spa |
dcterms.references | L. Nunes, N. Santos, and A. Rito Silva, “From a Monolith to a Microservices Architecture: An Approach Based on Transactional Contexts,” in 13th European Conference, ECSA 2019. Lectures Notes in Computer Science 11681, 2019, pp. 37–52, doi: 10.1007/978-3-030-29983-5_3. | spa |
dcterms.references | A. Homay, A. Zoitl, M. De Sousa, M. Wollschlaeger, and C. Chrysoulas, “Granularity cost analysis for function block as a service,” IEEE Int. Conf. Ind. Informatics, vol. 2019-July, pp. 1199–1204, 2019, doi: 10.1109/INDIN41052.2019.8972205 | spa |
dcterms.references | M. Cojocaru, A. Uta, and A. M. Oprescu, “MicroValid: A validation framework for automatically decomposed microservices,” in Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom, Dec. 2019, vol. 2019-Decem, pp. 78–86, doi: 10.1109/CloudCom.2019.00023. | spa |
dcterms.references | A. Christoforou, L. Odysseos, and A. Andreou, “Migration of Software Components to Microservices: Matching and Synthesis,” in Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering, 2019, pp. 134–146, doi: 10.5220/0007732101340146. | spa |
dcterms.references | I. Saidani, A. Ouni, M. W. Mkaouer, and A. Saied, “Towards Automated Microservices Extraction Using Muti-objective Evolutionary Search,” in 17th International Conference Service-Oriented Computing. Lectures Notes in computer science 11895, Oct. 2019, pp. 58–63, doi: 10.1007/978-3-030-33702-5_5. | spa |
dcterms.references | M. I. Josélyne, D. Tuheirwe-Mukasa, B. Kanagwa, and J. Balikuddembe, “Partitioning microservices - A Domain Engineering Approach,” in Proceedings of the 2018 International Conference on Software Engineering in Africa - SEiA ’18, 2018, pp. 43–49, doi: 10.1145/3195528.3195535. | spa |
dcterms.references | H. Vural, M. Koyuncu, and S. Misra, “A Case Study on Measuring the Size of Microservices,” in International Conference on Computational Science and Its Applications - ICCSA 2018, 2018, pp. 454–463, doi: 10.1007/b98054 | spa |
dcterms.references | S. Tyszberowicz, R. Heinrich, B. Liu, and Z. Liu, “Identifying Microservices Using Functional Decomposition,” in International Symposium on Dependable Software Engineering: Theories, Tools, and Applications, 2018, vol. 10998, pp. 50–65, doi: 10.1007/978-3-319-99933-3. | spa |
dcterms.references | A. A. C. De Alwis, A. Barros, A. Polyvyanyy, and C. Fidge, “Function-Splitting Heuristics for Discovery of Microservices in Enterprise Systems,” 2018, pp. 37–53. | spa |
dcterms.references | M. Tusjunt and W. Vatanawood, “Refactoring Orchestrated Web Services into Microservices Using Decomposition Pattern,” in 2018 IEEE 4th International Conference on Computer and Communications (ICCC), Dec. 2018, pp. 609–613, doi: 10.1109/CompComm.2018.8781036. | spa |
dcterms.references | Z. Ren et al., “Migrating web applications from monolithic structure to microservices architecture,” in ACM International Conference Proceeding Series, Sep. 2018, pp. 1–10, doi: 10.1145/3275219.3275230. | spa |
dcterms.references | W. Hasselbring and G. Steinacker, “Microservice architectures for scalability, agility and reliability in e-commerce,” in Proceedings - 2017 IEEE International Conference on Software Architecture Workshops, ICSAW 2017: Side Track Proceedings, 2017, pp. 243–246, doi: 10.1109/ICSAW.2017.11. | spa |
dcterms.references | J. P. Gouigoux and D. Tamzalit, “From monolith to microservices: Lessons learned on an industrial migration to a web oriented architecture,” in Proceedings - 2017 IEEE International Conference on Software Architecture Workshops, ICSAW 2017: Side Track Proceedings, 2017, pp. 62–65, doi: 10.1109/ICSAW.2017.35. | spa |
dcterms.references | D. Shadija, M. Rezai, and R. Hill, “Microservices: Granularity vs. Performance,” in UCC ’17 Companion Companion Proceedings of the10th International Conference on Utility and Cloud Computing, 2017, pp. 215–220, doi: 10.1145/3147234.3148093. | spa |
dcterms.references | S. Hassan, N. Ali, and R. Bahsoon, “Microservice Ambients: An Architectural Meta-Modelling Approach for Microservice Granularity,” in Proceedings - 2017 IEEE International Conference on Software Architecture, ICSA 2017, Apr. 2017, pp. 1–10, doi: 10.1109/ICSA.2017.32. | spa |
dcterms.references | L. Baresi, M. Garriga, and A. De Renzis, Microservices Identification through Interface Analysis, vol. 10465, no. November. Cham: Springer International Publishing, 2017. | spa |
dcterms.references | G. Mazlami, J. Cito, and P. Leitner, “Extraction of Microservices from Monolithic Software Architectures,” in 2017 IEEE International Conference on Web Services (ICWS), Jun. 2017, pp. 524–531, doi: 10.1109/ICWS.2017.61. | spa |
dcterms.references | G. Kecskemeti, A. Kertesz, and A. C. Marosi, “Towards a methodology to form microservices from monolithic ones,” in Euro-Par 2016 Workshops - Lecture Notes in Computer Science, 2017, vol. 10104 LNCS, pp. 284–295, doi: 10.1007/978-3-319-58943-5_23. | spa |
dcterms.references | S. Hassan and R. Bahsoon, “Microservices and their design trade-offs: A self-adaptive roadmap,” Proc. - 2016 IEEE Int. Conf. Serv. Comput. SCC 2016, pp. 813–818, 2016, doi: 10.1109/SCC.2016.113 | spa |
dcterms.references | M. Ahmadvand and A. Ibrahim, “Requirements Reconciliation for Scalable and Secure Microservice (De)composition,” in 2016 IEEE 24th International Requirements Engineering Conference Workshops (REW), Sep. 2016, pp. 68–73, doi: 10.1109/REW.2016.026. | spa |
dcterms.references | A. R. Hevner, S. T. March, J. Park, and S. Ram, “Design science in information systems research,” MIS Q., vol. 28, no. 1, pp. 75–105, 2004, Accessed: May 16, 2018. [Online]. Available: https://pdfs.semanticscholar.org/fa72/91f2073cb6fdbdd7c2213bf6d776d0ab411c.pdf. | spa |
dcterms.references | E. Evans, Domain-Driven Design Reference - Definitions and Pattern Summaries. 2015. | spa |
dcterms.references | L. Baresi, M. Garriga, and A. De Renzis, “Microservices identification through interface analysis,” in European Conference on Service-Oriented and Cloud Computing - Lecture Notes in Computer Science., Sep. 2017, vol. 10465 LNCS, pp. 19–33, doi: 10.1007/978-3-319-67262-5_2. | spa |
dcterms.references | J. Bogner, S. Wagner, and A. Zimmermann, “Towards a practical maintainability quality model for service-and microservice-based systems,” in Proceedings of the 11th European Conference on Software Architecture Companion Proceedings - ECSA ’17, 2017, vol. 3, pp. 195–198, doi: 10.1145/3129790.3129816. | spa |
dcterms.references | I. Candela, G. Bavota, B. Russo, and R. Oliveto, “Using cohesion and coupling for software remodularization: Is it enough?,” ACM Trans. Softw. Eng. Methodol., vol. 25, no. 3, May 2016, doi: 10.1145/2928268. | spa |
dcterms.references | D. Rud, A. Schmietendorf, and R. R. Dumke, “Product Metrics for Service-Oriented Infrastructures,” in Conference: Applied Software Measurement. Proceedings of the International Workshop on Software Metrics and DASMA Software Metrik Kongress (IWSM/MetriKon 2006), 2006, Accessed: Jun. 18,2019. [Online]. Available: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.122.6887&rep=rep1&type=pdf. | spa |
dcterms.references | Spacy.io, “Word Vectors and Semantic Similarity · spaCy Usage Documentation.” https://spacy.io/usage/vectors-similarity#basics (accessed Nov. 20, 2020). | spa |
dcterms.references | M. Hirzalla, J. Cleland-Huang, and A. Arsanjani, “A Metrics Suite for Evaluating Flexibility and Complexity in Service Oriented Architectures,” Springer, Berlin, Heidelberg, 2009, pp. 41–52. | spa |
dcterms.references | M. Cohn, User Stories applied for agile software development. Addison Wesley. Pearson Education Inc., 2004. | spa |
dcterms.references | M. Cohn, Agile Estimating and Planning. New York, NY, USA, 2005. | spa |
dcterms.references | K. Beck, Extreme Programming Explained: Embrace Change. Addison Wesley, 2000. | spa |
dcterms.references | J. Holland, Adaptation in natural and artificial systems. Michigan: University of Michigan Press, 1975 | spa |
dcterms.references | F. Herrera, M. Lozano, and J. L. Verdegay, Algoritmos Genéticos: Fundamentos, Extensiones y Aplicaciones. ProQuest, 1995. | spa |
dcterms.references | mybatis.org, “Mybatis Jpetstore-6: A web application built on top of MyBatis 3, Spring 3 and Stripes.” https://github.com/mybatis/jpetstore-6 (accessed Nov. 22, 2020). | spa |
dcterms.references | E. Evans, Domain-Driven Design. Addison Wesley, 2004. | spa |
dcterms.references | M. I. Rahman, S. Panichella, and D. Taibi, “A Curated Dataset of Microservices-Based Systems,” in Joint Proceedings of the Inforte Summer School on Software Maintenance and Evolution (CEUR Workshop Proceedings; Vol. 2520). CEUR-WS., 2019, vol. 2520, Accessed: Feb. 14, 2020. [Online]. Available: http://research.tuni.fi/clowee. | spa |
dcterms.references | G. Marquez and H. Astudillo, “Actual Use of Architectural Patterns in Microservices-Based Open Source Projects,” in Proceedings - Asia-Pacific Software Engineering Conference, APSEC, Jul. 2018, vol. 2018-December, pp. 31–40, doi: 10.1109/APSEC.2018.00017. | spa |
dcterms.references | M. Perepletchikov, C. Ryan, and K. Frampton, “Cohesion Metrics for Predicting Maintainability of Service-Oriented Software,” in Seventh International Conference on Quality Software (QSIC 2007), 2007, pp. 328–335, doi: 10.1109/QSIC.2007.4385516. | spa |
dc.identifier.doi | 10.1109/ACCESS.2021.3106342 | |
dc.relation.citationendpage | 25 | spa |
dc.relation.citationissue | (2017) | spa |
dc.relation.citationstartpage | 1 | spa |
dc.relation.citationvolume | 20 | spa |
dc.relation.cites | Wang, F. , Zhang, J. (2022) IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) | |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
dc.rights.creativecommons | Atribución-NoComercial 4.0 Internacional (CC BY-NC 4.0) | spa |
dc.subject.proposal | Service-oriented systems engineering | eng |
dc.subject.proposal | Service computing | eng |
dc.subject.proposal | Software design | eng |
dc.subject.proposal | Software architecture | eng |
dc.subject.proposal | Web services | eng |
dc.subject.proposal | Micro-services granularity | eng |
dc.subject.proposal | Microservices decompositions | eng |
dc.subject.proposal | Genetic algorithms | eng |
dc.subject.proposal | Software metrics | eng |
dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | spa |
dc.type.content | Text | spa |
dc.type.driver | info:eu-repo/semantics/article | spa |
dc.type.redcol | http://purl.org/redcol/resource_type/ART | spa |
oaire.accessrights | http://purl.org/coar/access_right/c_abf2 | spa |
oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | spa |
dc.type.version | info:eu-repo/semantics/publishedVersion | spa |