Modeling of software development process with the Markov processes




Markov processes, Markov chains, software development, association rule mining


The comparative analysis of the existing research on the application of formal approaches to the software development process modeling is performed. Based on the analysis, the urgency of modeling of the software development process as a Markov random process is substantiated. An information model of association rule mining and application in software development is developed. The information model represents the process and can be used in the design of appropriate information technology. The research, which determined the number of steps needed to develop one software component and the whole software is carried out.

The levels of detail of the software development process such as the level, representing the development of software, which is a finite set of software components; the level, representing a detailed description of the stages of development of a particular component; the level, representing a detailed description a certain stage of development of a particular component are identified. For each level, the relevant stages of software development are described. Modeling of the software development process with the Markov chains is conducted. This will allow using a single mathematical tool to represent the corresponding process at different levels of detail

Author Biographies

Tamara Savchuk, Vinnytsia National Technical University Khmelnytske highway, 95, Vinnytsia, Ukraine, 21021

PhD, Associate Professor

Department of computer science

Nataliia Pryimak, Vinnytsia National Technical University Khmelnytske highway, 95, Vinnytsia, Ukraine, 21021

Postgraduate student

Department of computer science


  1. Herbsleb, J. D., Moitra, D. (2001). Global software development. IEEE Software, 18 (2), 16–20. doi: 10.1109/52.914732
  2. Aho, A. V., Ullman, J. D. (1972). The Theory of Parsing, Translation, and Compiling. Vol. 1. New Jersy: Prentice Hall, 147–151.
  3. Peterson, J. L. (1981). Petri net theory and the modeling of systems. New Jersy: Prentice Hall, 310.
  4. Harel, D. (1987). Statecharts: a visual formalism for complex systems. Science of Computer Programming, 8 (3), 231–274. doi: 10.1016/0167-6423(87)90035-9
  5. uz Zaman, Q., Sindhu, M. A., Nadeem, A. (2015). Formalizing a Use Case to a Kripke Structure. Software Engineering and Applications/ 831: Advances in Power and Energy Systems. doi: 10.2316/p.2015.829-017
  6. Stirling, C. (1991). Modal and temporal logics. GB.: University of Edinburgh, Department of Computer Science, 23–30.
  7. Sindhu, M. (2013). Algorithms and Tools for Learning-based Testing of Reactive Systems. Stockholm, 19.
  8. Fraser, G., Wotawa, F. (2007). Using model-checkers to generate and analyze property relevant test-cases. Software Quality Journal, 16 (2), 161–183. doi: 10.1007/s11219-007-9031-6
  9. Dranidis, D., Tigka, K., Kefalas, P. (2003). Formal modelling of use cases with X-machines. Proceedings of the 1st South-East European Workshop on Formal Methods, SEEFM'03, 72–83.
  10. Holcombe, M. (1988). X-machines as a basis for dynamic system specification. Software Engineering Journal, 3 (2), 69. doi: 10.1049/sej.1988.0009
  11. Kolesnikova, E. V., Negri, A. A. (2013). Transformatsiia kognitivnyh kart v modeli markovskih protsesov dlya proektov sozdaniia programnogo obespecheniia. Managing the development of complex systems, 15, 30–35.
  12. Koshkin, K. V., Makeev, S. A., Fomenko, G. V. (2011). Kognitivnie modeli upravleniia zhilishchno-komunalnym hozaystvom kak aktivnoy sistemoy. Managing the development of complex systems, 5, 17–19.
  13. Tihonov, V. I., Mironov, M. A. (1977). Markovskie procesy. Мoscow: Soviet radio, 488.
  14. Markov, A. V. (2011). Sovokupnoe ispolzovanie setey Petri I UML diagram pri razrabotke programmnogo obespechenia. Sbornik nauchnyh trudov NGTU, 2 (64), 85–94.
  15. Meier, P., Kounev, S., Koziolek, H. (2011). Automated Transformation of Component-Based Software Architecture Models to Queueing Petri Nets. 2011 IEEE 19th Annual International Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems. doi: 10.1109/mascots.2011.23
  16. Jie, T. W., Ameedeen, M. A. (2015). A Model Driven method to represent Free Choice Petri Nets as Sequence Diagram. 2015 4th International Conference on Software Engineering and Computer Systems (ICSECS). doi: 10.1109/icsecs.2015.7333104
  17. Singh, H., Pal, P. (2013). Software Reliability Testing using Monte Carlo Methods. International Journal of Computer Applications, 69 (4), 41–44. doi: 10.5120/11834-7554
  18. Martin, R. (2003). Agile Software Development: Principles, Patterns, and Practices. New Jersy: Prentice Hall, 102–103.
  19. What are the Software Development Life Cycle (SDLC) phases? Available at:
  20. Gorban, І. (2003). Teoriia imovirnostei i matematychna statystyka dlia naukovyh pratsivnykiv ta inzheneriv. Kyiv, 90–110.
  21. Everett, G. D. (2007). Software Testing: Testing Across the Entire Software Development Life Cycle. Wiley-IEEE Computer Society Press, 280.
  22. Fundamentalnii protsess testirovaniia. Available at:
  23. Savchuk, T. O., Pryymak, N. V. (2015). Poshuk asotsiativnyh pravil dlia pryiniatiia rishen v marketyngovii diyalnosti, 3, 196–199.




How to Cite

Savchuk, T., & Pryimak, N. (2017). Modeling of software development process with the Markov processes. Eastern-European Journal of Enterprise Technologies, 3(2 (87), 33–38.