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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An approach to the translation of natural language business rules into sql table constraints
(2021) Orlovskyi, D. L.; Kopp, A. M.
An approach to build a decentralized collection of business process models
(Publisher Individual entrepreneur Picha Y. V., 2021) Kopp, A. M.; Orlovskyi, D. L.; Orekhov, Sergey Valerievich
In this study we have proposed the approach to organization of decentralized blockchain-based business process model repository that could be used to provide secure software solution to store and access the business process model collection in a tamper-resistant manner.
Towards the alignment between database security framework and business process maturity model
(Одеська національна академія харчових технологій, 2021) Kopp, A. M.; Orlovskyi, D. L.
This paper considers the extension and improvement of database security framework by means of its alignment with business process maturity model in order to provide the holistic tool for organizations that are planning to establish a database security system, as well as to assess and ensure its quality using the well-known scale of maturity levels.
Towards an approach to decentralized storage and exchange of business process models
(2021) Kopp, A. M.; Orlovskyi, D. L.
This paper proposes an approach to decentralized storage and exchange of business process models using the blockchain technology and tokenization approach. There was proposed an idea of the Ethereum smart contract that implements the non-fungible token extended with syntactic and semantic properties, which can be used to evaluate quality and estimate value of tokenized business process models.
General Issues of Applications Architecture Domain Design
(2021) Kopp, A. M.; Orlovskyi, D. L.; Ersoyleyen, D.
Applications architecture domain as a part of enterprise 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, 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, the most error-prone stage of the whole software engineering project. It is well-known,that design shortcomings made on the applications 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.
An Approach and Software Prototype for Translation of Natural Language Business Rules into Database Structure
(CEUR Workshop Proceedings, 2021) Kopp, A. M.; Orlovskyi, D. L.; Orekhov, Sergey Valerievich
In the recent decades data has indeed become one of the most valuable assets for government institutions, private businesses, and individual persons. Nowadays almost any software, from social networks and dating mobile applications to large information systems and analytical services for enterprise management, accumulates, stores, and processes data to solve certain problems in their subject areas. Extremely large data volumes are organized in databases that are used as the baseline for almost all of modern software applications. As the most important components of software systems, databases should be carefully designed, since drawbacks at the stage of requirements elicitation may result in exponential growth of defects fixing costs at testing and maintenance phases. Therefore, this study proposes an approach and software tool to database schema generation from textual requirements also known in database design domain as business rules. This may help database designers to rapidly obtain usable database schemas in order to detect and fix defects as early as possible. Moreover, proposed solution may simplify the database design process, since database creation scripts are generated from business rules directly. Thus, instead of coding all the required statements, engineers are only need to check obtained schema and make certain adjustments to data types, unique attributes, or used naming style. This research considers relational model and relational databases, since they are most widely used nowadays. State-of-the-art analysis is made, proposed approach is described in details, software tool with its brief usage examples is described, conclusions are made, and further research directions are formulated.
An Approach to Development of Interactive Adaptive Software Tool to Support Data Analysis Activity
(CEUR Workshop Proceedings, 2021) Orlovskyi, D. L.; Kopp, A. M.; Bilous, I. S.
In the recent decades, databases have been used in any field of human activity to keep valuable data about ongoing processes. Large amounts of data stored in enterprise databases are useless without having a specialized software tool for data discovery or querying. Most business users that make data-driven decisions usually do not have special training and experience in database querying using special formal languages. Existing solutions are based on "query wizards" and database query forms that require knowledge of a database schema and inconvenient for users without special training. Proposed approach is based on the content-based filtering of already executed queries by usage frequency and similarity criteria in order to suggest relevant queries that may be re-used. It is a baseline of the interactive adaptive system for data analysis, which design and development is outlined in this study. Software prototype was demonstrated and its usage was discussed. Conclusions were made and future research was formulated.
A Business Intelligence Dashboard Design Approach to Improve Data Analytics and Decision Making
(CEUR Workshop Proceedings, 2020) Orlovskyi, D. L.; Kopp, A. M.
This paper considers a problem of dashboard design in order to improve data analytics and decision making as business intelligence capabilities. Essentials of data warehouses and data marts used as data sources for business intelligence activities are briefly outlined, and the star schema data structure is considered as the most widely used. Data visualization is considered from the perspective of proper visualization graphs and charts selection. It is extremely vital for designed dashboards, since inappropriate visuals may mislead users and shift their focus to wrong things. Bar charts, line charts, and pie charts are considered as the most common visualization graphs. Proposed approach includes two phases: dataset preparation and dataset analysis. While dataset preparation is mostly focused on star schema transformation into flat structures, dataset analysis phase proposes recommendations on which visualizations may be placed on a designed dashboard. In order to propose such recommendations, threshold values of dataset sizes are used. A dashboard design process, which is considered as the baseline of the proposed dashboard design approach, is outlined. Sample dataset in considered, five data subsets are prepared and recommendations on visualization charts for these datasets, which may be placed on a dashboard, are proposed. Obtained results are discussed, conclusions are made, as well as the further research objectives in this field are formulated.
Towards the Generalized Criterion for Evaluation of Business Process Model Quality
(CEUR Workshop Proceedings, 2020) Kopp, A. M.; Orlovskyi, D. L.
Business process management has become the most widely-used and reliable approach to organizational management over the last decades. It is also considered as a part of quality management system in an organization. Business process modeling is the core of business process management, which is used for visualization, analysis, and improvement of organizational activities. Moreover, business process modeling plays an important role in the context of business process management maturity of an overall enterprise. Therefore, this paper is focused on the problem of business process model quality evaluation. Existing approaches based on the process modeling guidelines, measures and corresponding thresholds are reviewed, as well as the refined process modeling rules, corresponding quality criteria, the generalized quality criterion, and thresholds for its translation into linguistic values are proposed. The data model and software prototype are developed and the validation results are outlined.
Enterprise Architecture Modeling Support based on Data Extraction from Business Process Models
(CEUR Workshop Proceedings, 2020) Orlovskyi, D. L.; Kopp, A. M.
This paper presents a problem of enterprise architecture artifacts extraction from business process model collections, which organizations of higher maturity levels tend to manage, in order to build the architecture landscape and apply enterprise architecture management practices. Existing enterprise architecture frameworks, languages, and methodologies are discussed. Proposed approach is based on mapping between business process and enterprise architecture elements in order to present all business architecture artifacts in a single coarse-grained model. The software implementation allows generating business architecture landscapes that could be used for architecture evolution purposes, such as transformation planning or maintenance efforts evaluation.