Improvement of the method for solving the task of early identification of information system configuration items
DOI:
https://doi.org/10.34185/1562-9945-3-164-2026-05Keywords:
information system, configuration item, early identification task, function, architectural entity, DBSCAN, architecture descriptionAbstract
This study investigates the process that controls the IT project configuration.
The study addressed the problem of early identification of configuration items (CI) within an enterprise management information system (IS). Modern research in this area is mainly aimed at solving the task of services early identification during refactoring of software systems. The issue of applying artificial intelligence methods and, in particular, clustering to detect CI at the early stages of the IS life cycle has not been studied sufficiently.
The aim of the study is to develop a new or improve an existing method for solving the task of early identification of IS CI.
To achieve the aim of the study, the existing method of synthesizing descriptions of rational architecture creating IS based on descriptions of functional requirements for this IS was improved. The essence of this improvement is to use the DBSCAN clustering algorithm to detect architectural entities as clusters of individual IS functions. The results of solving the clustering task make it possible to simplify the description of the architecture creating IS by significantly reducing the number of CIs, provided that descriptions of architectural entities as clusters of individual IS functions will act as CIs.
The main features of the course and results of the experimental verification of the improved method are considered. The descriptions of ten functions of the task “Formation and maintenance of an individual plan of a scientific and pedagogical employee of the department” were used as the derived data for this verification. The result of using the method is three solution options, presented in the form of sets of one or two clusters. These options describe monolithic, modular and service-oriented IS architecture.
The use of the obtained results allows you to automate the procedure for synthesizing the description of the IS architecture. This automation will increase the quality of IS development by allocating a set of architectural entities of this IS for design. This set is much smaller than the set of elementary IS functions.
References
Guide to the Software Engineering Body of Knowledge. Version 3.0 / eds. Bourque P., Fairley R.E. Washington, DC, United States: IEEE Computer Society, 2014. 335 p.
Quigley J.M., Robertson K.L. Configuration Management, Second Edition: Theory and Application for Engineers, Managers, and Practitioners. New York: Auerbach Publications, 2019. 453 p. DOI: https://doi.org/10.1201/9780429318337
Farayola O.A., Hassan A.O., Adaramodu O.R., Fakeyede O.G., Oladeinde M. Configuration management in the modern era: best practices, innovations, and challenges. Computer Science & IT Research Journal. 2023. Vol. 4, No 2. P. 140-157. DOI: https://doi.org/10.51594/csitrj.v4i2.613
Kozhanov A., Ievlanov M. Definition a clusterization method to solve the task of early identification of IT product configuration elements. Eastern-European Journal of Enterprise Technologies. 2026. Vol. 1. №. 2 (139). P. 77–90. DOI: https://doi.org/10.15587/1729-4061.2026.352878
Faitelson D., Heinrich R., Tyszberowicz Sh. Supporting software architecture evolution by functional decomposition. In 5th International Conference on Model-Driven Engineering and Software Development – MODELSWARD. SciTePress, 2017. P. 435-442. DOI: https://doi.org/10.5220/0006206204350442
Cadavid H., Andrikopoulos V., Avgeriou P., Chris Broekema P. System and software architecting harmonization practices in ultra-large-scale systems of systems: A confirmatory case study. Information and Software Technology. 2022. Vol. 150. № 106984. DOI: https://doi.org/10.1016/j.infsof.2022.106984
Felfernig A., Le V., Popescu A., Uta M., Tran T.N., Atas M. (2021). An Overview of Re-commender Systems and Machine Learning in Feature Modeling and Configuration. Proceed-ings of the 15th International Working Conference on Variability Modelling of Software-Intensive Systems (VaMoS '21). New York, NY, USA: Association for Computing Machinery, 2021. Article 16, P. 1–8. DOI: https://doi.org/10.1145/3442391.3442408
Abolfazli A., Spiegelberg J., Palmer G., Anand A. A Deep Reinforcement Learning Approach to Configuration Sampling Problem. 2023 IEEE International Conference on Data Mining (ICDM). Shanghai, China, 2023. P. 1-10. DOI: https://doi.org/10.1109/ICDM58522.2023.00009.
Sellami Kh., Saied M.A., Ouni A. A Hierarchical DBSCAN Method for Extracting Microservices from Monolithic Applications. EASE '22: Proceedings of the 26th International Conference on Evaluation and Assessment in Software Engineering. New York, NY, USA: Association for Computing Machinery, 2022. P. 201-210. DOI: https://doi.org/10.1145/3530019.3530040
Krause A., Zirkelbach C., Hasselbring W., Lenga S., Kroger D. Microservice Decomposi-tion via Static and Dynamic Analysis of the Monolith. 2020 IEEE International Conference on Software Architecture Companion (ICSA-C). Salvador, Brazil, 2020. P. 9-16. DOI: https://doi.org/10.1109/ICSA-C50368.2020.00011
Ievlanov, M., Vasiltcova, N., Neumyvakina, O., Panforova, I. Development of a method for solving the problem of it product configuration analysis. Eastern-European Journal of En-terprise Technologies. 2022. Vol. 6. Iss. 2 (120). P. 6–19. DOI: https://doi.org/10.15587/1729-4061.2022.269133
Santos J.L., Martins L.E.G., Molléri J.S. Requirements extraction from model-based systems engineering: A systematic literature review. Journal of Systems and Software. 2025. Vol. 226. № 112407. DOI: https://doi.org/10.1016/j.jss.2025.112407
Evlanov М. Development of the model and method of selecting the description of rational architecture of information system. Eastern-European Journal of Enterprise Technologies. 2016. Vol. 1, No. 2(79). P. 4–12. DOI: https://doi.org/10.15587/1729-4061.2016.60583
Han J., Kamber M., Pei J. Data Mining. Concepts and Techniques. (Third Edition). Waltham: Morgan Kaufmann Publishers. 2011. URL: https://shop.elsevier.com/books/data-mining-concepts-and-techniques/han/978-0-12-381479-1 (дата звернення 21.03.2026).
Schubert E., Sander J., Ester M., Kriegel H.P., Xu, X. DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN. ACM Transactions on Database Systems. 2017. Vol. 42. Iss. 3. Article No.: 19, P. 1-21. DOI: https://doi.org/10.1145/3068335.
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