Метод автоматизації процесу розрахунку показників надійності програмних систем та їх компонентів
dc.citation.epage | 8 | |
dc.citation.issue | 1 | |
dc.citation.journalTitle | Український журнал інформаційних технологій | |
dc.citation.spage | 1 | |
dc.citation.volume | 6 | |
dc.contributor.affiliation | Національний університет “Львівська політехніка” | |
dc.contributor.affiliation | Lviv Polytechnic National University | |
dc.contributor.author | Сенів, М. М. | |
dc.contributor.author | Seniv, M. M. | |
dc.coverage.placename | Львів | |
dc.coverage.placename | Lviv | |
dc.date.accessioned | 2025-05-21T08:02:05Z | |
dc.date.created | 2024-02-28 | |
dc.date.issued | 2024-02-28 | |
dc.description.abstract | Проаналізовано існуючі засоби розрахунку показників надійності програмних систем. Встановлено, що для визначення показників надійності програмних систем доцільно використовувати структурно – логічний аналіз блок-схем надійності, оскільки він наочно та найбільш адекватно відображає процес розрахунку показників надійності програмної системи загалом та її компонентів зокрема. Не зважаючи на зовнішню простоту такого аналізу, його проведення не є тривіальною задачею, адже навіть побудова умови працездатності технічної системи є непростим завданням, особливо у випадку наявності багатьох елементів з різноплановими зв'язками між ними, при розв'язанні якої вручну існує дуже велика ймовірність людської помилки. Також побудова та візуалізація графа станів/переходів є нетривіальною задачею, оскільки кількість можливих станів програмної системи залежно від кількості елементів зростає експоненційно, та, своєю чергою збільшує складність системи диференціальних рівнянь, розв'язок якої дає змогу розрахувати необхідні показники надійності. Визначено, що процес надійнісного проектування складних програмних систем загалом, та їх компонентів зокрема, потребує автоматизації усіх його етапів, починаючи від складання блок-схеми надійності (reliability block diagram, RBD), і закінчуючи візуалізацією отриманих результатів. Розроблено метод автоматизації процесу розрахунку показників надійності програмних систем та їх компонентів, який складається з восьми кроків, та, на відміну від існуючих, дає змогу проектанту інтуїтивно зрозуміло вводити не тільки вхідні дані про структуру а й саму архітектуру ПЗ з точки зору його надійності, а також автоматизує всі етапи розрахунку показників надійності, від етапу побудови блок-схеми надійності до етапу знаходження розподілу ймовірностей перебування програмної системи у всіх можливих станах. Запропонований метод дає можливість використовувати в різній комбінації методи, алгоритми та програмні засоби, які використовуються для надійнісного проектування саме програмних систем та вибрати з них найбільш адекватні потребам користувача в конкретній ситуації. Використання розробленого методу дає можливість зменшити вплив людського фактора та імовірності внесення помилки в процесі розрахунку показників надійності програмних систем на всіх етапах надійнісного проектування та скоротити час його проведення як мінімум на 21 %. | |
dc.description.abstract | The existing means of calculating reliability indicators of software systems are analyzed. It has been established that to determine the reliability indicators of software systems, it is advisable to use the structural-logical analysis of reliability block diagrams, since it clearly and most adequately reflects the process of calculating the reliability indicators of the software system as a whole and its components in particular. Despite the external simplicity of such an analysis, conducting it is not a trivial task, because even building the condition of technical system operability is a difficult task, especially in the case of the presence of many elements with various connections between them, when solving which manually there is a very high probability human error. Also, the construction and visualization of the graph of states / transitions is a nontrivial task, since the number of possible states of the software system depending on the number of elements grows exponentially, and, in turn, increases the complexity of the system of differential equations, the solution of which makes it possible to calculate the necessary reliability indicators. It was determined that the process of reliability design of complex software systems in general, and their components in particular, requires automation of all its stages, starting from the compilation of the reliability block diagram (RBD), and ending with the visualization of the obtained results. A method of automating the process of calculating the reliability indicators of software systems and their components has been developed, which consists of eight steps and, unlike the existing ones, allows the designer to intuitively enter not only input data about the structure, but also the software architecture itself from the point of view of its reliability, and also automates all stages of calculating reliability indicators, from the stage of constructing a reliability block diagram to the stage of finding the distribution of probabilities of the software system being in all possible states. The proposed method makes it possible to use in various combinations the methods, lgorithms and software tools used for the reliability design of software systems and to choose from them the most adequate to the needs of the user in a specific situation. The use of the developed method makes it possible to reduce the influence of the human factor and the probability of making an error in the process of calculating reliability indicators of software systems at all stages of reliability design and to reduce its time by at least 21 %. | |
dc.format.extent | 1-8 | |
dc.format.pages | 8 | |
dc.identifier.citation | Сенів М. М. Метод автоматизації процесу розрахунку показників надійності програмних систем та їх компонентів / М. М. Сенів // Український журнал інформаційних технологій. — Львів : Видавництво Львівської політехніки, 2024. — Том 6. — № 1. — С. 1–8. | |
dc.identifier.citationen | Seniv M. M. A method of automating the process of calculating reliability indicators of software systems and their components / M. M. Seniv // Ukrainian Journal of Information Tecnology. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 6. — No 1. — P. 1–8. | |
dc.identifier.doi | doi.org/10.23939/ujit2024.01.001 | |
dc.identifier.uri | https://ena.lpnu.ua/handle/ntb/64845 | |
dc.language.iso | uk | |
dc.publisher | Видавництво Львівської політехніки | |
dc.publisher | Lviv Politechnic Publishing House | |
dc.relation.ispartof | Український журнал інформаційних технологій, 1 (6), 2024 | |
dc.relation.ispartof | Ukrainian Journal of Information Tecnology, 1 (6), 2024 | |
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dc.relation.referencesen | 1. ISO/IEC 25010:2011 Systems and software engineering – Systems and software Quality Requirements and Evaluation (SQuaRE) – System and software quality models," 2011. [Online]. Available: https://www.iso.org/obp/ui/#iso:std:iso-iec:25010:ed-1:v1:en | |
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dc.relation.referencesen | 3. Bharathi, R, & Selvarani, R. (2019). "Software Reliability Assessment of Safety Critical System Using Computational Intelligence." International Journal of Software Science and Computational Intelligence, 11(3): 1‑25. https://doi.org/10.4018/ijssci.2019070101 | |
dc.relation.referencesen | 4. Teslyuk, V, Sydor, A, Karovič, V ml., Pavliuk, O, & Kazymyra, I. (2021). Modelling Reliability Characteristics of Technical Equipment of Local Area Computer Networks. Electronics, 10(8):955. https://doi.org/10.3390/electronics10080955 | |
dc.relation.referencesen | 5. Li, Y F., Huang, H Z., Mi, J. et al. (2022). Reliability analysis of multi-state systems with common cause failures based on Bayesian network and fuzzy probability. Ann Oper Res, 311, 195‑209. https://doi.org/10.1007/s10479-019-03247-6 | |
dc.relation.referencesen | 6. Ozirkovskyy, L., Volochiy, B., Zmysnyi, M., & Shkiliuk, O. (2020). SYNTHESIS OF SAFE BEHAVIOR ALGORITHMS OF RADIOELECTRONIC SYSTEMS FOR CRITICAL APPLICATIONS. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 10(1), 28‑31. https://doi.org/10.35784/iapgos.913 | |
dc.relation.referencesen | 7. Sydor, A. R., Teslyuk, V. M., & Denysyuk, P. Y. (2014). Recurrent expressions for reliability indicators of compound electropower systems. Technical Electrodynamics, 4, 47‑49. | |
dc.relation.referencesen | 8. Teslyuk, V., Pavliuk, O. & Kazymyra, I. (2021). Model for Determining the Optimal Structure of Hierarchical Asymmetric Branched Computer Networks, 2021 IEEE 32nd International Conference on Microelectronics (MIEL), Nis, Serbia, 2021, pp. 259–262, https://doi.org/10.1109/MIEL52794.2021.9569115 | |
dc.relation.referencesen | 9. Karnouskos, S., Sinha, R., Leitão, P., Ribeiro, L., & Strasser, T. I. (2018). The Applicability of ISO/IEC 25023 Measures to the Integration of Agents and Automation Systems," IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, Washington, DC, USA, 2927–2934. https://doi.org/10.1109/IECON.2018.8592777 | |
dc.relation.referencesen | 10. Catelani, M., Ciani, L., & Venzi, M. (2015). Reliability assessment for complex systems: A new approach based on RBD models, 2015 IEEE International Symposium on Systems Engineering (ISSE), Rome, Italy, 286–290. https://doi.org/10.1109/SysEng.2015.7302771 | |
dc.relation.referencesen | 11. Sahinoglu, M., & Ramamoorthy, C. V. (2005). RBD tools using compression, decompression, hybrid techniques to code, decode, and compute reliability in simple and complex embedded systems, Oct. 2005 IEEE Transactions on Instrumentation and Measurement, 54(5), 1789–1799. https://doi.org/10.1109/TIM.2005.855103 | |
dc.relation.referencesen | 12. Bennetts, R. G. (1982). Analysis of Reliability Block Diagrams by Boolean Techniques, June 1982 IEEE Transactions on Reliability, R-31(2), 159–166. https://doi.org/10.1109/TR.1982.5221283 | |
dc.relation.referencesen | 13. Babu, Naveen, Himagiri, Krishna, V Vamshi , Kumar, A Anil , & Ravi, M. (2019). Software Defect Prediction Analysis by Using Machine Learning Algorithms. International Journal of Recent Technology and Engineering 8(2S11). 3544‑3546. https://doi.org/10.35940/ijrte.b1438.0982s1119 | |
dc.relation.referencesen | 14. Libo, Li, Lessmann, Stefan, & Baesens, Bart (2019). Evaluating Software Defect Prediction Performance: An Updated Benchmarking Study. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3312070 | |
dc.relation.referencesen | 15. Revoori Veeharika Reddy, Nagella Kedharnath, Mandi Akif Hussain, & S. Vidya. (2021). Software Defect Estimation using Machine Learning Algorithms. International Journal of Recent Technology and Engineering (IJRTE), 10(1), 204–208. https://doi.org/10.35940/ijrte.A5898.0510121 | |
dc.relation.referencesen | 16. Balogun, Abdullateef O., Basri, Shuib, Mahamad, Saipunidzam, Abdulkadir, Said J., & Bajeh, Amos O. (2020). Impact of Feature Selection Methods on the Predictive Performance of Software Defect Prediction Models: An Extensive Empirical Study". Symmetry, 12(7), 1147–1156. https://doi.org/10.3390/sym12071147 | |
dc.relation.referencesen | 17. LEI, T., XUE, J., WANG, Y., NIU, Z., SHI, Z., & ZHANG, Y. (2022). WCM-WTrA: A Cross-Project Defect Prediction Method Based on Feature Selection and Distance-Weight Transfer Learning. Chinese Journal of Electronics, 31, 354–366. https://doi.org/10.1049/cje.2021.00.119 | |
dc.relation.referencesen | 18. Jiarpakdee, J., Tantithamthavorn, C., & Treude, C. (2020). The impact of automated feature selection techniques on the interpretation of defect models. Empir Software Eng., 25, 3590–3638. https://doi.org/10.1007/s10664-020-09848-1 | |
dc.relation.referencesen | 19. Rahul, Hans, & Kaur, Harjot (2020). Opposition-Based Enhanced Grey Wolf Optimization Algorithm for Feature Selection in Breast Density Classification. International Journal of Machine Learning and Computing, 10(3), 458‑64. https://doi.org/10.18178/ijmlc.2020.10.3.957 | |
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dc.rights.holder | © Національний університет “Львівська політехніка”, 2024 | |
dc.subject | програмне забезпечення | |
dc.subject | блок-схема надійності | |
dc.subject | надійнісне проєктування | |
dc.subject | граф станів та переходів | |
dc.subject | software | |
dc.subject | RBD | |
dc.subject | reliability | |
dc.subject | states and transitions graph | |
dc.subject.udc | 004.05 | |
dc.title | Метод автоматизації процесу розрахунку показників надійності програмних систем та їх компонентів | |
dc.title.alternative | A method of automating the process of calculating reliability indicators of software systems and their components | |
dc.type | Article |
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