Кафедра "Програмна інженерія та інтелектуальні технології управління ім. А. В. Дабагяна"

Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/1665

Офіційний сайт кафедри http://web.kpi.kharkov.ua/asu

Від січня 2022 року кафедра має назву "Програмна інженерія та інтелектуальні технології управління ім. А. В. ДАБАГЯНА" (тоді ж, у січні 2022 року в окремий підрозділ виділилася кафедра "Інформаційні системи та технології"), попередні назви – "Програмна інженерія та інформаційні технології управління" (від 2015), "Автоматизовані системи управління" (від 1977); первісна назва – кафедра автоматичного управління рухом.

Кафедра автоматичного управління рухом заснована в 1964 році задля підготовки інженерів-дослідників у галузі автоматичного управління рухом з ініціативи професора Харківського політехнічного інституту Арега Вагаршаковича Дабагяна та генерального конструктора КБ "Електроприладобудування" Володимира Григоровича Сергєєва.

Кафедра входить до складу Навчально-наукового інституту комп'ютерних наук та інформаційних технологій Національного технічного університету "Харківський політехнічний інститут".

У складі науково-педагогічного колективу кафедри працюють: 4 доктора технічних наук; 24 кандидата наук: 22 – технічних, 1 – фізико-математичних, 1 – економічних, 1 – доктор філософії; 3 співробітників мають звання професора, 19 – доцента, 1 – старшого наукового співробітника.

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  • Ескіз
    Публікація
    Using machine learning to assess the compliance of business process models with textual descriptions
    (Національний авіаційний університет, 2024) Rudskyi, O. V.; Kopp, Andrii Mykhailovych
    This article discusses the problem of comparing business process models with their textual descriptions. This article employs a Systematic Literature Review (SLR) methodology to explore methods for comparing textual descriptions with business process models, aiming to enhance accuracy, identify discrepancies, and foster a common understanding among stakeholders.
  • Ескіз
    Публікація
    An approach to analysis of ArchiMate application architecture models using the software coupling metric
    (Національний технічний університет "Харківський політехнічний інститут", 2021) Kopp, Andrii Mykhailovych; Orlovskyi, Dmytro Leonidovych; Ersoyleyen, Dorukhan
    Applications architecture is the baseline of any organizational activity, which main goal is to provide the executional environment for business processes in order to deliver products or services to satisfy customer needs and generate revenue. Nowadays, large software engineering projects always begin with the architecture design phase, despite the waterfall or agile methodology is used by a software development team. Applications architecture design is the most important and, at the same time, error-prone stage of the whole software engineering project. It is well-known that design shortcomings made on the design phase may increase drastically to testing and maintenance phases. Further costs to defects fixing may be hundred times higher in the later project stages in compare to the design stage on which applications architecture is defined. Common system design solutions, which were proven on practice and used in many projects, are known as architectural patterns. Software architecture patterns are considered as building block for system implementation. The most popular and efficient way to share architectural patterns are graphical models that used as any other blueprints of engineering solutions. Applications architecture models are built to represent system design, whereas, such models are already based on certain patterns as the industry best practices. Hence, in this paper we consider a relevant problem of applications architecture models analysis, which relevance is defined by those fact that designed blueprints of information systems and other software solutions should be carefully checked for all presumable inefficiencies in order to avoid extra efforts and related costs for defects fixing in the later project stages. It is proposed to use ArchiMate enterprise architecture modeling language, since it can be used not only to represent applications architecture, but is connection to business and technology layers. In order to evaluate applications architecture models, respective ArchiMate metamodel is considered and represented as labeled directed graph, and coupling software metric is selected for analysis. Sample calculations are demonstrated, obtained results are discussed, conclusion and future work directions are formulated.
  • Ескіз
    Публікація
    Applications architecture analysis based on design patterns and image recognition
    (ТОВ "Планета-Прінт", 2021) Kopp, Andrii Mykhailovych; Orlovskyi, Dmytro Leonidovych; Ersoyleyen, D.
  • Ескіз
    Публікація
    Adaptive query interface as a data analysis tool
    (ТОВ "Планета-Прінт", 2021) Orlovskyi, Dmytro Leonidovych; Kopp, Andrii Mykhailovych; Bilous, I. S.
  • Ескіз
    Публікація
    Using blockchain and non-fungible tokens to implement decentralized repository of enterprise models
    (ТОВ "Планета-Прінт", 2021) Kopp, Andrii Mykhailovych; Orlovskyi, Dmytro Leonidovych
  • Ескіз
    Публікація
    Information technology for power equipment monitoring
    (ТОВ "Планета-Прінт", 2021) Orlovskyi, Dmytro Leonidovych; Kopp, Andrii Mykhailovych; Syzonova, K. H.
  • Ескіз
    Публікація
    Capturing software requirements for business process model analysis and improvement
    (Національний технічний університет "Харківський політехнічний інститут", 2020) Kopp, Andrii Mykhailovych; Orlovskyi, Dmytro Leonidovych
    This paper considers the problem of software requirements capturing for business process model evaluation and recommendations generation to suggest how detected modeling errors may be eliminated in order to improve business process model correctness. Existing software tools for business process model analysis are based on metrics and thresholds that allow assume presence of errors in business process models, but they are not capable to recommend structural changes required to eliminate detected modeling errors. Therefore, business process model analysis and improvement tasks become relevant, since early detection and elimination of possible errors presented in business process models may allow organizations avoid extra costs that may occur on any of the steps of business process lifecycle. Since business process models are shared organizational assets, it is also necessary to consider the capabilities of collaborative and concurrent usage of business process models by multiple stakeholders. Hence, the workflow of business process model analysis and improvement was analyzed and its key steps, which describe expected user and software behavior, were formalized using the IDEF0 functional model. Functional software requirements were captured in the form of user stories according to modern agile practices of software development. These user stories are based on features and drawbacks of existing software tools for business process model analysis. Captured user stories were formalized using the use case modeling. Non-functional software requirements were also captured; they include maintainability, readability, testability, understandability, integrability, and complexity requirements. Captured requirements can be used to design and develop business process model analysis and improvement software capable to provide recommendations to eliminate detected modeling errors.