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Modelling and Data Analysis
2020. Vol. 10, no. 1, 140–156
https://doi.org/10.17759/mda.2020100109
ISSN: 2219-3758 / 2311-9454 (online)

Software Quality Problems

 
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Abstract

We consider the “ever-living” problem of software quality, which is even more acute because software products are built into everything that can or cannot be. What is meant by quality? What is its criteria? Is it possible to measure it? What hinders quality and how to improve it?

General Information

Keywords: Software quality, quality standards, reliability, usability, security, quality assessment, quality management, training in quality development

Journal rubric: Software

OpenAlex citations: 1

OpenAlex trends: Advanced Data Processing Techniques, Software Reliability and Analysis Research, Engineering Education and Technology

Information about the work in OpenAlex

Number of citations: 1

Topics

Advanced Data Processing Techniques

This cluster of papers focuses on the modeling and control of multidimensional systems, with an emphasis on redundant transmission, fuzzy controller adaptation, fault tolerance, real-time systems, and energy efficiency in various domains such as cyber-physical systems, network traffic analysis, and industrial automation.

Number of works: 60256  |  Total number of citations: 206829

Topic detailsв OpenAlex

Software Reliability and Analysis Research

This cluster of papers focuses on the assessment and prediction of software reliability, utilizing architecture-based approaches, testing-effort dependent models, neural networks, and fault detection and correction processes. It also explores the reliability of component-based systems, NHPP models, open source software, and sensitivity analysis using Markov chain models.

Number of works: 36547  |  Total number of citations: 321647

Topic detailsв OpenAlex

Engineering Education and Technology

This cluster of papers explores the concept of Smart University within the context of Digital Ecosystems, focusing on topics such as Internet of Things, Artificial Intelligence, cognitive modeling, educational technology, innovation management, predictive maintenance, knowledge management, and industrial control systems. The papers discuss the principles and semantics of digital ecosystems, machine learning algorithms for smart data analysis, ontology of smart classrooms, mobile social networking for smart campuses, and the development and evaluation models for smart universities.

Number of works: 12917  |  Total number of citations: 36014

Topic detailsв OpenAlex

Work details in OpenAlex

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2020100109

Published

For citation: Lukin, V.N. (2020). Software Quality Problems. Modelling and Data Analysis, 10(1), 140–156. (In Russ.). https://doi.org/10.17759/mda.2020100109

© Lukin V.N., 2020

License: CC BY-NC 4.0

References

  1. Kuper A. Psikhbol’nitsa v rukakh patsientov. – SPb: SimvoL–Plyus, 2004.
  2. Platt D. Soft – otstoi! I chto s ehtim delat’? – SPb: SimvoL–Plyus, 2007.
  3. Glass R. Programmirovanie i konfl ikty 2.0. – SPb: SimvoL–Plyus, 2010.
  4. Lukin V.V., Lukin V.N., Lukin T.V. Tekhnologiya razrabotki programmnogo obes-pecheniya: ucheb. posobie. – 4–e izd. – M.: Vuzovskaya kniga, 2019. – 294 p.: il.
  5. Standarty: http://www.gost.ru/, obnovleniya i novye: http://protect.gost.ru/.
  6. Standarty: ISO/IEC 25000:2014(en) Systems and software engineering – Systems and software Quality Requirements and Evaluation (SQuaRE) – Guide to SQuaRE
  7. Standarty: ISO/IEC 25010:2011 Systems and software engineering – Systems and software Quality Requirements and Evaluation (SQuaRE) – System and software quali-ty models GOST R ISO/MEHK 25010–2015 Informatsionnye tekhnologii. Sistem-naya i programmnaya inzheneriya. Trebovaniya i otsenka kachestva sistem i programm-nogo obespecheniya (SQuaRE). Modeli kachestva sistem i programmnykh produktov.
  8. Standarty: GOST R ISO/MEHK 9126–93. Otsenka programmnoi produktsii. Kharak-teristiki kachestva i rukovodstva po ikh primeneniyu.
  9. Reinvoter Dzh. Kak pasti kotov. Nastavlenie dlya programmistov, rukovodyashchikh drugimi programmistami. – SPb.: Piter, 2008.
  10. Terekhov A.N. Tekhnologiya programmirovaniya: Uchebnoe posobie. – M.: InterneT–Universitet Informatsionnykh Tekhnologii; BINOM. Laboratoriya znanii, 2006.
  11. Bystritskii N.D. Metodika i instrumental’noe sredstvo otsenki korrektnosti funktsionirovaniya informatsionnykh resursov: Diss. … kand. tekhnicheskikh nauk, 2018.
  12. Glass R. Fakty i zabluzhdeniya professional’nogo programmirovaniya. – SPb: SimvoL–Plyus, 2008.
  13. Lukin V.N., Bakhirkin M.V. Dinamicheskaya otsenka vremeni razrabotki programm-nykh sistem. Monografi ya. – M.: Izd-vo MAI, 2019. – 160 p.: il.
  14. Bakhirkin M.V., Zinchenko A.S., Kirpichnikov A.P., Lukin V.N., Tkachenko D.P. Model’ dinamicheskoi otsenki stoimostnykh, vremennykh i funktsional’nykh poka-zatelei protsessa proektirovaniya i razrabotki programm i programmnykh sistem. Vestnik Kazanskogo tekhnologicheskogo universiteta. 2014, t.17, № 7, pp. 284–290.
  15. Zotova A.A., Lukin V.N. Pol’zovatel’skii interfeis: istoriya i sovremennost’. «Novye informatsionnye tekhnologiI». Tezisy dokladov XV Mezhdunarodnoi stu-dencheskoi shkoly-seminara – M.: MIEHM, 2007. – pp. 50–55.
  16. Didziguri D.G., Lukin V.N. Problemy postroeniya pol’zovatel’skogo interfei-sa dlya slabovidyashchikh. Modelirovanie i analiz dannykh: Trudy fakul’teta infor-matsionnykh tekhnologii MGPPU; vyp. 3 – M.: MGPPU, 2007. – pp. 51–59.
  17. Lukin V.N. Podgotovka kachestvennykh programmistov: problemy obucheniya. Modelirovanie i analiz dannykh: nauchnyi zhurnal. 2017, № 1. – M., 2017, pp. 29–41.
  18. Lukin V.N. Kachestvennye programmy kak predmet obucheniya. Modelirovanie i analiz dannykh: Trudy fakul’teta informatsionnykh tekhnologii MGPPU; vyp. 4 – M.: MGPPU, 2009. – pp. 54–65.
  19. Kaufman V.Sh. Nisha zanyatosti deesposobnykh veteranov: https://kaufmanict.eu/ideas/Privychnologija_vs_nedomyslije.htm

Information About the Authors

Vladimir N. Lukin, Candidate of Science (Physics and Matematics), Docent, Moscow Aviation Institute (National Research University), Professor of Applied Informatics Department, Faculty of Information Technologies, Moscow State University of Psychology and Education, Moscow, Russian Federation, ORCID: https://orcid.org/0000-0001-8906-2686, e-mail: lukinvn@list.ru

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