DESIGNING INFORMATION SUPPORT FOR EVALUATING THE QUALITY OF EMBEDDED SOFTWARE

Authors

DOI:

https://doi.org/10.20998/2079-0023.2020.01.20

Keywords:

decision-making, fuzzy logic, embedded systems, software quality, software assessments, software testing

Abstract

This article presents a system for evaluating the quality of embedded software using a decision system based on fuzzy logic. These approaches will improve the assessment of software quality, due to its features. This article defines the main criteria for software quality used in assessing the quality of the software. The main literature was examined, in which fuzzy logic was described, decision-making systems using fuzzy logic, as well as software quality assessment systems, including software for embedded systems. The main characteristics and properties of embedded syst ems were considered. Based on the considered characteristics and properties of embedded systems, the ranking of criteria was made, which will be further used in the software quality assessment methodology. The main criteria that are used to evaluate the quality of software were considered, and the criteria presented were distributed according to the degree of influence on the assessment of the quality of software of embedded systems. Fuzzy logic was considered, and more precisely: the basic properties of fuzzy logic and fuzzy numbers, the basic mathematical operators applied to fuzzy numbers. The system for constructing rules for the rule base, as well as the defuzzification process, built on the basis of the centroid method, is analyzed. An example of software evaluation for embedded systems was considered. In this example, linguistic variables were determined, as well as their numerical ranges, which were used for the initial assessment of the quality criteria of this software. Each range of ratings was distributed according to the influence of a criterion on software quality. The output linguistic variable and its numerical value were also determined. In the end, based on the set values, an estimate of the set software was derived. The theoretical result obtained in this article is the basis for constructing a system for evaluating software quality for embedded systems.

Author Biographies

Vladyslav Ivanovich Zybin, National Technical University «Kharkiv Polytechnic Institute»

National Technical University «Kharkiv Polytechnic Institute», student of the Department of Software Engineering and Information Technology Management; Kharkiv city, Ukraine

Iryna Victorivna Liutenko, National Technical University "Kharkiv Polytechnic Institute"

Candidate of Engineering Sciences, National Technical University "Kharkiv Polytechnic Institute", Associate Professor, Department of Software Engineering and Management Information Technology; Kharkiv, Ukraine

References

ISO/IEC 25010. Available at: http://iso25000.com/index.php/en/iso25000- standards/iso-25010 (accessed 27.04.2020).

Zadeh L. A. Fuzzy Sets. Information and control 1965, vol. 8, pp. 338–353.

Gieseckea S., Hasselbringa W., Riebischb M. Classifying architectural constraints as a basis for software quality assessment. Advanced Engineering Informatics. 2007, vol. 21, issue 2, pp. 169– 179.

Siavvas M. G., Chatzidimitriou K. C., Symeonidis A. L. QATCH - An adaptive framework for software product quality assessment. Expert Systems with Applications. 2017, vol. 86, pp. 350–366.

Pasrija V., Kumar S., Srivastava P. R. Assessment of Software Quality: Choquet Integral Approach. Procedia Technology. 2012, vol. 6, pp. 153–162.

Ahrem A. A., Ashinyants M. R., Petrov S. A. Nechetkij logicheskij vyvod v sisteme prinyatiya reshenij [Fuzzy inference in the decisionmaking system]. Trudy ISA RAN [Proceedings of ISA RAN]. 2007, vol. 29, pp. 265–275.

Gorbachenko I. M. Ocenka kachestva programmnogo obespecheniya dlya sozdaniya sistem testirovaniya [Quality assessment of software for creating testing systems]. Fundamental'nye issledovaniya [Basic research]. 2013, no. 6 (part 4), pp 823–827.

Klyuev E.I., Grinenko E.A. Podhod k ocenke kachestva programmnyh sredstv [Approach to software quality assessment]. Inzheneriia prohramnoho zabespechennia [Software Security Engineering]. 2014, no. 3 (19), pp. 5–14.

Garousia V., Feldererbe M., Karapıçakc Ç. M., Yılmazd U. Testing embedded software: A survey of the literature. Information and Software Technology. 2018, vol. 104, pp. 14–45.

Mehmood N., Petersen M. K., BörstlerJ., Wnuk K. Regression testing for large-scale embedded software development – Exploring the state of practice. Information and Software Technology. 2020, vol. 120, article 106243.

Seo J., Choi B., Yang S. Lightweight embedded software performance analysis method by kernel hack and its industrial field study. Journal of Systems and Software. 2012, vol. 85, issue 1, pp. 28–42.

Burakov V. V. Metodika ocenki kachestva programmnyh sredstv [Software Quality Assessment Methodology]. Izvestiya vysshih uchebnyh zavedenij. Priborostroenie [News of higher educational institutions. Instrumentation]. 2008, vol. 51, no. 1, pp. 35–41.

Pronina O. I., Patykop E. E. Ispol'zovanie nechetkih mnozhestv pri opredelenii klassa avtomobilya [Using fuzzy sets when determining a car class]. Visnyk Natsionalnoho tekhnichnoho universytetu «KhPI»: zbirnyk naukovykh prats. Seriia: Systemnyi analiz, upravlinnia ta informatsiini tekhnolohii [Bulletin of the National Technical University "KhPI": a collection of scientific papers. Series: Systems Analysis, Control and Information Technology]. 2017, no. 28 (1250), pp. 41–48.

Rutkovska D., Pilinski M., Rutkovski L. Sieci neuronowe, algorytmy genetyczne i systemy rozmyte. Warszawa, Łodż, Wydawnictwo Naukowe PWN, 2004. 410 s. (Russ. ed.: Rutkovska D., Pilinski M., Rutkovski L. Nejronnye seti, geneticheskie algoritmy i nechetkie sistemy. Moscow, Goryachaya liniya - Telekom Publ., 2006. 452 p.).

Grinyaev Yu. V. Teoriya nechetkih mnozhestv. Uchebnoe posobie dlya studentov [Theory of fuzzy sets. Study guide for students]. Tomsk, Tomskij gosudarstvennyj universitet sistem upravleniya i radioelektroniki Publ., 2008. 141 p.

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How to Cite

Zybin, V. I., & Liutenko, I. V. (2020). DESIGNING INFORMATION SUPPORT FOR EVALUATING THE QUALITY OF EMBEDDED SOFTWARE. Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, (1 (3), 124–130. https://doi.org/10.20998/2079-0023.2020.01.20

Issue

No. 1 (3) (2020)

Section

INFORMATION TECHNOLOGY

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