09. Gushchina O. A. The use of intelligent systems for risk management in software projects

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UDC 004.413.4

DOI: 10.15507/0236-2910.027.201702.250-263

The use of intelligent systems for risk management in software projects

Oksana A. Gushchina
Associate Professor of the Department of Computer Aided Design Systems, Faculty of Mathematics and Information Technology, National Research Mordovia State University (68 Bolshevistskaya St., Saransk 430005, Russia), Ph.D. (Engineering), ORCID: http://orcid.org/0000-0003-2978-9028, This email address is being protected from spambots. You need JavaScript enabled to view it.

Introduction: The article identifies the main risks of a software project, examines the use of different types of intelligent systems in the risk management process for software projects, discusses the basic methods used for process estimation and forecasting in the field of software engineering, identifies currently used empty expert systems, software systems for analysis and risk management of software projects.
Materials and Methods: The author describes the peculiarities of risk management in the field of software engineering with involvement of intelligent systems. The intelligent techniques allow solving the control task with expert precision without the involvement of human experts.
Results: The result of this work: – identification of the key risks of a software project (tax, legal, financial and commercial risks, IT risks, personnel risks, risks related to competitors, suppliers, marketing and demand and market); – investigation of the current, applied to risk management of software system projects, artificial intelligence, particularly expert systems and software tools for evaluation of the process results; – identification of the most popular empty expert systems (Clips, G2 and Leonardo) and software products of the analysis of large databases (Orange, Weka, Rattle GUI, Apache Mahout, SCaViS, RapidMiner, Databionic ESOM Tools, ELKI, KNIME, Pandas and UIMA); – consideration of the cluster, correlation, regression, factor and dispersion analysis methods for the estimation and prediction of the processes of software engineering.
Discussion and Conclusions: The results show the feasibility of the application of various intelligent systems in the risk management process. The analysis of methods of evaluating risks and the tendency of their application in the modern systems of intellectual analysis can serve as a start point for creating a unified system of risk management for software projects of medium and high complexity with a predetermined structure of the project.

Keywords: software project management, artificial intelligence systems, expert systems

For citation: Gushchina O. A. The use of intelligent systems for risk management in software projects. Vestnik Mordovskogo universiteta = Mordovia University Bulletin. 2017; 2(27):250-263. DOI: 10.15507/0236-2910.027.201702.250-263

This work is licensed under a Creative Commons Attribution 4.0 License.