Development of an intelligent agent for analysis of nonfunctional characteristics in specifications of software requirements

Authors

DOI:

https://doi.org/10.15587/1729-4061.2019.154074

Keywords:

specification of software requirements, nonfunctional characteristics of software, intelligent agent based on the ontological approach

Abstract

One of the urgent present-day tasks consists in ensuring an automated analysis of specifications of software requirements for sufficiency of information on nonfunctional component characteristics of software quality. Analysis of known intelligent agents based on the ontological approach has shown that these agents do not solve the problem of quantifying sufficiency of information in the specification of software requirements for determining nonfunctional characteristics of software.

The objective of this study was to implement the intelligent agent based on the ontological approach for analyzing information on nonfunctional characteristics in specifications of software requirements.

A model of intelligent agent activity has been developed based on the ontological approach for evaluating specifications of software requirements. It reflects features of assessing information sufficiency for determining nonfunctional component characteristics of software quality. The developed model is a theoretical basis for implementing the intelligent agent based on the ontological approach for evaluating specifications of software requirements.

The intelligent agent based on the ontological approach has been implemented for evaluating information on nonfunctional characteristics in the specifications of software requirements. The implemented agent forms conclusions on sufficiency or insufficiency of information about nonfunctional component characteristics of software quality in the specification of requirements to actual software. In addition, it quantifies the level of information sufficiency in the specification of requirements to actual software for determining each of nonfunctional characteristics of software and determining all nonfunctional component characteristics of software quality in aggregate. The agent provides a list of attributes that should supplement the specification of requirements for increasing the level of sufficiency of its information as well as visualization of gaps in knowledge of all nonfunctional component characteristics of software quality.

The results of functioning of the implemented agent have shown an increase in the level of information sufficiency in the specification of software requirements. The developed intelligent agent makes it possible to partially eliminate human participation in information processing, avoid loss of essential information and minimize occurrence of errors at the early stages of the software life cycle.

Author Biographies

Tetiana Hovorushchenko, Khmelnytskyi National University Instytutska str., 11, Khmelnytskyi, Ukraine, 29016

Doctor of Technical Sciences, Senior Researcher, Associate Professor, Head of Department

Department of Computer Engineering & System Programming

Olga Pavlova, Khmelnytskyi National University Instytutska str., 11, Khmelnytskyi, Ukraine, 29016

Postgraduate Student

Department of Computer Engineering & System Programming

Mykyta Bodnar, Khmelnytskyi National University Instytutska str., 11, Khmelnytskyi, Ukraine, 29016

Postgraduate Student

Department of Computer Engineering & System Programming

References

  1. Hastie, S., Wojewoda, S. Standish Group 2015 Chaos Report – Q&A with Jennifer Lynch. Available at: http://www.infoq.com/articles/standish-chaos-2015
  2. McConnell, S. (2013). Code complete. Redmond, 896.
  3. Levenson, N. G. (2012). Engineering a safer world: systems thinking applied to safety. Cambridge, 560.
  4. Cruickshank, K. J. (2009). A validation metrics framework for safety-critical software-intensive systems. Monterey, 144.
  5. Hovorushchenko, T., Pomorova, O. (2018). Information technology of evaluating the sufficiency of information on quality in the software requirements specifications. CEUR-WS, 2104, 555–570. Available at: http://ceur-ws.org/Vol-2104/paper_228.pdf
  6. ISO/IEC 25010:2011. Systems and Software Engineering. Systems and Software Quality Requirements and Evaluation (SQuaRE). System and Software Quality Models (2011). Geneva, 34.
  7. Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5 (2), 199–220. doi: https://doi.org/10.1006/knac.1993.1008
  8. Burov, E. (2014). Complex ontology management using task models. International Journal of Knowledge-Based and Intelligent Engineering Systems, 18 (2), 111–120. doi: https://doi.org/10.3233/KES-140291
  9. Burov, E., Pasitchnyk, V., Gritsyk, V. (2014). Modeling software testing processes with task ontologies. British Journal of Education and Science, 2 (6), 256–263.
  10. Assawamekin, N., Sunetnanta, T., Pluempitiwiriyawej, C. (2009). Ontology-based multiperspective requirements traceability framework. Knowledge and Information Systems, 25 (3), 493–522. doi: https://doi.org/10.1007/s10115-009-0259-2
  11. Kof, L., Gacitua, R., Rouncefield, M., Sawyer, P. (2010). Ontology and Model Alignment as a Means for Requirements Validation. 2010 IEEE Fourth International Conference on Semantic Computing. doi: https://doi.org/10.1109/icsc.2010.95
  12. Bajnaid, N. O., Benlamri, R., Pakstas, A., Salekzamankhani, Sh. (2016). An ontological approach to model software quality assurance knowledge domain. Lecture Notes on Software Engineering, 4 (3), 193–198.
  13. Hovorushchenko, T., Pomorova, O. (2016). Ontological approach to the assessment of information sufficiency for software quality determination. CEUR-WS, 1614, 332–348.
  14. Wooldridge, M., Jennings, N. R. (1995). Intelligent agents: theory and practice. The Knowledge Engineering Review, 10 (2), 115–152. doi: https://doi.org/10.1017/s0269888900008122
  15. Freitas, A., Bordini, R. H., Vieira, R. (2017). Model-driven engineering of multi-agent systems based on ontologies. Applied Ontology, 12 (2), 157–188. doi: https://doi.org/10.3233/ao-170182
  16. Ossowska, K., Szewc, L., Weichbroth, P., Garnik, I., Sikorski, M. (2016). Exploring an Ontological Approach for User Requirements Elicitation in the Design of Online Virtual Agents. Lecture Notes in Business Information Processing, 40–55. doi: https://doi.org/10.1007/978-3-319-46642-2_3
  17. Lezcano-Rodriguez, L. A., Guzman-Luna, J. A. (2016). Ontological characterization of basics of KAOS chart from natural language. ITECKNE, 13 (2), 157–168. doi: https://doi.org/10.15332/iteckne.v13i2.1482
  18. García-Magariño, I., Gómez-Sanz, J. J. (2013). An Ontological and Agent-Oriented Modeling Approach for the Specification of Intelligent Ambient Assisted Living Systems for Parkinson Patients. Lecture Notes in Computer Science, 11–20. doi: https://doi.org/10.1007/978-3-642-40846-5_2
  19. Rakib, A., Faruqui, R. U. (2013). A Formal Approach to Modelling and Verifying Resource-Bounded Context-Aware Agents. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 86–96. doi: https://doi.org/10.1007/978-3-642-36642-0_9
  20. Michalowski, W., O’Sullivan, D., Farion, K., Sayyad-Shirabad, J., Kuziemsky, C., Kukawka, B., Wilk, S. (2013). A Task-based Support Architecture for Developing Point-of-care Clinical Decision Support Systems for the Emergency Department. Methods of Information in Medicine, 52 (01), 18–32. doi: https://doi.org/10.3414/me11-01-0099
  21. Michael, J. B., Man-Tak Shing, Cruickshank, K. J., Redmond, P. J. (2010). Hazard Analysis and Validation Metrics Framework for System of Systems Software Safety. IEEE Systems Journal, 4 (2), 186–197. doi: https://doi.org/10.1109/jsyst.2010.2050159
  22. Baker, R., Habli, I. (2013). An Empirical Evaluation of Mutation Testing for Improving the Test Quality of Safety-Critical Software. IEEE Transactions on Software Engineering, 39 (6), 787–805. doi: https://doi.org/10.1109/tse.2012.56
  23. ISO 25023:2016. Systems and Software Engineering. Systems and Software Quality Requirements and Evaluation (SQuaRE). Measurement of System and Software Product Quality (2016). Geneva, 45.
  24. Hovorushchenko, T., Pavlova, O. (2019). Method of Activity of Ontology-Based Intelligent Agent for Evaluating Initial Stages of the Software Lifecycle. Recent Developments in Data Science and Intelligent Analysis of Information, 169–178. doi: https://doi.org/10.1007/978-3-319-97885-7_17
  25. ISO/IEC/IEEE 29148:2011. Systems and Software Engineering. Life Cycle Processes. Requirements Engineering (2011). Geneva, 28.

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Published

2019-01-14

How to Cite

Hovorushchenko, T., Pavlova, O., & Bodnar, M. (2019). Development of an intelligent agent for analysis of nonfunctional characteristics in specifications of software requirements. Eastern-European Journal of Enterprise Technologies, 1(2), 6–17. https://doi.org/10.15587/1729-4061.2019.154074